SAS Output

Chapter 10b: Descriptive Statistics for Time-Varying Variables

The MEANS Procedure

symptoms
posaff

symptoms: Time-Varying Physical Symptoms
posaff: Time-Varying Positive Affect

2752

2747

1.6609738

2.5802694

1.4296401

0.7319597

0

5.0000000

4.0000000

Ch 10b: Empty Means, Single-Level Model for the Variance for Symptoms

Independent Observations

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	symptoms
Covariance Structure	Diagonal
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Residual

Dimensions
Covariance Parameters	1
Columns in X	1
Columns in Z	0
Subjects	1
Max Obs per Subject	2752

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2752
Number of Observations Not Used	0

Covariance Parameter Estimates
Cov Parm	Estimate	Standard Error	Z Value	Pr > Z
Residual	2.0431	0.05508	37.09	<.0001

Fit Statistics
-2 Log Likelihood	9776.1
AIC (Smaller is Better)	9780.1
AICC (Smaller is Better)	9780.1
BIC (Smaller is Better)	9791.9

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
9776.1	2	9780.1	9780.1	9784.4	9791.9	9793.9

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	1.6610	0.02725	2751	60.96	<.0001	0.05	1.6075	1.7144

Ch 10b: Empty Means, Two-Level Model for the Variance for Symptoms

Sessions Within Burst*Persons

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	symptoms
Covariance Structure	Unstructured
Subject Effect	PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	2
Columns in X	1
Columns in Z per Subject	1
Subjects	462
Max Obs per Subject	6

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2752
Number of Observations Not Used	0

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	9776.09222302
1	2	7772.47351641	0.00000016
2	1	7772.47329585	0.00000000

Convergence criteria met.

Estimated V Correlation Matrix for PersonID*burst 101 1
Row	Col1	Col2	Col3
1	1.0000	0.6933	0.6933
2	0.6933	1.0000	0.6933
3	0.6933	0.6933	1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr > Z
UN(1,1)	PersonID*burst	1.4250	0.1010	14.10	<.0001
Residual		0.6303	0.01863	33.82	<.0001

Fit Statistics
-2 Log Likelihood	7772.5
AIC (Smaller is Better)	7778.5
AICC (Smaller is Better)	7778.5
BIC (Smaller is Better)	7790.9

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
1	2003.62	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
7772.5	3	7778.5	7778.5	7783.4	7790.9	7793.9

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	1.6699	0.05758	460	29.00	<.0001	0.05	1.5568	1.7831

Eq 10b.5: Empty Means, Three-Level Model for the Variance for Symptoms

Level-1 Sessions Within Level-2 Bursts Within Level-3 Persons

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	symptoms
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	3
Columns in X	1
Columns in Z per Subject	6
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2752
Number of Observations Not Used	0

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	9776.09222302
1	3	7524.75262478	0.00017433
2	1	7524.52944403	0.00000062
3	1	7524.52867842	0.00000000

Convergence criteria met.

Estimated V Matrix for PersonID 101
Row	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13	Col14	Col15	Col16	Col17	Col18	Col19	Col20	Col21	Col22	Col23	Col24	Col25	Col26	Col27
1	2.1333	1.5029	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
2	1.5029	2.1333	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
3	1.5029	1.5029	2.1333	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
4	1.0773	1.0773	1.0773	2.1333	1.5029	1.5029	1.5029	1.5029	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
5	1.0773	1.0773	1.0773	1.5029	2.1333	1.5029	1.5029	1.5029	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
6	1.0773	1.0773	1.0773	1.5029	1.5029	2.1333	1.5029	1.5029	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
7	1.0773	1.0773	1.0773	1.5029	1.5029	1.5029	2.1333	1.5029	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
8	1.0773	1.0773	1.0773	1.5029	1.5029	1.5029	1.5029	2.1333	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
9	1.0773	1.0773	1.0773	1.5029	1.5029	1.5029	1.5029	1.5029	2.1333	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
10	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	2.1333	1.5029	1.5029	1.5029	1.5029	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
11	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.5029	2.1333	1.5029	1.5029	1.5029	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
12	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.5029	1.5029	2.1333	1.5029	1.5029	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
13	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.5029	1.5029	1.5029	2.1333	1.5029	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
14	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.5029	1.5029	1.5029	1.5029	2.1333	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
15	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.5029	1.5029	1.5029	1.5029	1.5029	2.1333	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
16	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	2.1333	1.5029	1.5029	1.5029	1.5029	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
17	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.5029	2.1333	1.5029	1.5029	1.5029	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
18	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.5029	1.5029	2.1333	1.5029	1.5029	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
19	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.5029	1.5029	1.5029	2.1333	1.5029	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
20	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.5029	1.5029	1.5029	1.5029	2.1333	1.5029	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
21	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.5029	1.5029	1.5029	1.5029	1.5029	2.1333	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773
22	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	2.1333	1.5029	1.5029	1.5029	1.5029	1.5029
23	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.5029	2.1333	1.5029	1.5029	1.5029	1.5029
24	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.5029	1.5029	2.1333	1.5029	1.5029	1.5029
25	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.5029	1.5029	1.5029	2.1333	1.5029	1.5029
26	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.5029	1.5029	1.5029	1.5029	2.1333	1.5029
27	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.0773	1.5029	1.5029	1.5029	1.5029	1.5029	2.1333

Estimated V Correlation Matrix for PersonID 101
Row	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13	Col14	Col15	Col16	Col17	Col18	Col19	Col20	Col21	Col22	Col23	Col24	Col25	Col26	Col27
1	1.0000	0.7045	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
2	0.7045	1.0000	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
3	0.7045	0.7045	1.0000	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
4	0.5050	0.5050	0.5050	1.0000	0.7045	0.7045	0.7045	0.7045	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
5	0.5050	0.5050	0.5050	0.7045	1.0000	0.7045	0.7045	0.7045	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
6	0.5050	0.5050	0.5050	0.7045	0.7045	1.0000	0.7045	0.7045	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
7	0.5050	0.5050	0.5050	0.7045	0.7045	0.7045	1.0000	0.7045	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
8	0.5050	0.5050	0.5050	0.7045	0.7045	0.7045	0.7045	1.0000	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
9	0.5050	0.5050	0.5050	0.7045	0.7045	0.7045	0.7045	0.7045	1.0000	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
10	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	1.0000	0.7045	0.7045	0.7045	0.7045	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
11	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.7045	1.0000	0.7045	0.7045	0.7045	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
12	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.7045	0.7045	1.0000	0.7045	0.7045	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
13	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.7045	0.7045	0.7045	1.0000	0.7045	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
14	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.7045	0.7045	0.7045	0.7045	1.0000	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
15	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.7045	0.7045	0.7045	0.7045	0.7045	1.0000	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
16	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	1.0000	0.7045	0.7045	0.7045	0.7045	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
17	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.7045	1.0000	0.7045	0.7045	0.7045	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
18	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.7045	0.7045	1.0000	0.7045	0.7045	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
19	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.7045	0.7045	0.7045	1.0000	0.7045	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
20	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.7045	0.7045	0.7045	0.7045	1.0000	0.7045	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
21	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.7045	0.7045	0.7045	0.7045	0.7045	1.0000	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050
22	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	1.0000	0.7045	0.7045	0.7045	0.7045	0.7045
23	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.7045	1.0000	0.7045	0.7045	0.7045	0.7045
24	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.7045	0.7045	1.0000	0.7045	0.7045	0.7045
25	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.7045	0.7045	0.7045	1.0000	0.7045	0.7045
26	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.7045	0.7045	0.7045	0.7045	1.0000	0.7045
27	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.5050	0.7045	0.7045	0.7045	0.7045	0.7045	1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr > Z
UN(1,1)	PersonID	1.0773	0.1692	6.37	<.0001
UN(1,1)	PersonID*burst	0.4255	0.04036	10.54	<.0001
Residual		0.6305	0.01864	33.82	<.0001

Fit Statistics
-2 Log Likelihood	7524.5
AIC (Smaller is Better)	7532.5
AICC (Smaller is Better)	7532.5
BIC (Smaller is Better)	7543.3

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
2	2251.56	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
7524.5	4	7532.5	7532.5	7536.9	7543.3	7547.3

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	1.7047	0.1064	104	16.03	<.0001	0.05	1.4938	1.9156

Likelihood Ratio Test for FitEmpty2S vs. FitEmpty3S

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitEmpty2S	7772.5	3	7778.5	7790.9	.	.	.
FitEmpty3S	7524.5	4	7532.5	7543.3	247.945	1	0

Ch 10b: Empty Means, Single-Level Model for the Variance for Positive Affect

Independent Observations

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	posaff
Covariance Structure	Diagonal
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Residual

Dimensions
Covariance Parameters	1
Columns in X	1
Columns in Z	0
Subjects	1
Max Obs per Subject	2747

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2747
Number of Observations Not Used	5

Covariance Parameter Estimates
Cov Parm	Estimate	Standard Error	Z Value	Pr > Z
Residual	0.5356	0.01445	37.06	<.0001

Fit Statistics
-2 Log Likelihood	6080.4
AIC (Smaller is Better)	6084.4
AICC (Smaller is Better)	6084.4
BIC (Smaller is Better)	6096.2

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
6080.4	2	6084.4	6084.4	6088.6	6096.2	6098.2

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	2.5803	0.01396	2746	184.79	<.0001	0.05	2.5529	2.6076

Ch 10b: Empty Means, Two-Level Model for the Variance for Positive Affect

Sessions Within Burst*Persons

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	posaff
Covariance Structure	Unstructured
Subject Effect	PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	2
Columns in X	1
Columns in Z per Subject	1
Subjects	462
Max Obs per Subject	6

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2747
Number of Observations Not Used	5

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	6080.35610255
1	2	3974.72299429	0.00000002
2	1	3974.72298456	0.00000000

Convergence criteria met.

Estimated V Correlation Matrix for PersonID*burst 101 1
Row	Col1	Col2	Col3
1	1.0000	0.7070	0.7070
2	0.7070	1.0000	0.7070
3	0.7070	0.7070	1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr > Z
UN(1,1)	PersonID*burst	0.3795	0.02675	14.19	<.0001
Residual		0.1573	0.004653	33.80	<.0001

Fit Statistics
-2 Log Likelihood	3974.7
AIC (Smaller is Better)	3980.7
AICC (Smaller is Better)	3980.7
BIC (Smaller is Better)	3993.1

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
1	2105.63	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
3974.7	3	3980.7	3980.7	3985.6	3993.1	3996.1

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	2.5806	0.02965	462	87.03	<.0001	0.05	2.5224	2.6389

Eq 10b.5: Empty Means, Three-Level Model for the Variance for Positive Affect

Level-1 Sessions Within Level-2 Bursts Within Level-3 Persons

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	posaff
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	3
Columns in X	1
Columns in Z per Subject	6
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2747
Number of Observations Not Used	5

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	6080.35610255
1	2	3576.96355010	0.00000075
2	1	3576.96299494	0.00000000

Convergence criteria met.

Estimated V Matrix for PersonID 101
Row	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13	Col14	Col15	Col16	Col17	Col18	Col19	Col20	Col21	Col22	Col23	Col24	Col25	Col26	Col27
1	0.5380	0.3806	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
2	0.3806	0.5380	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
3	0.3806	0.3806	0.5380	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
4	0.3163	0.3163	0.3163	0.5380	0.3806	0.3806	0.3806	0.3806	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
5	0.3163	0.3163	0.3163	0.3806	0.5380	0.3806	0.3806	0.3806	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
6	0.3163	0.3163	0.3163	0.3806	0.3806	0.5380	0.3806	0.3806	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
7	0.3163	0.3163	0.3163	0.3806	0.3806	0.3806	0.5380	0.3806	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
8	0.3163	0.3163	0.3163	0.3806	0.3806	0.3806	0.3806	0.5380	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
9	0.3163	0.3163	0.3163	0.3806	0.3806	0.3806	0.3806	0.3806	0.5380	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
10	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.5380	0.3806	0.3806	0.3806	0.3806	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
11	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3806	0.5380	0.3806	0.3806	0.3806	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
12	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3806	0.3806	0.5380	0.3806	0.3806	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
13	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3806	0.3806	0.3806	0.5380	0.3806	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
14	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3806	0.3806	0.3806	0.3806	0.5380	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
15	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3806	0.3806	0.3806	0.3806	0.3806	0.5380	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
16	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.5380	0.3806	0.3806	0.3806	0.3806	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
17	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3806	0.5380	0.3806	0.3806	0.3806	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
18	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3806	0.3806	0.5380	0.3806	0.3806	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
19	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3806	0.3806	0.3806	0.5380	0.3806	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
20	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3806	0.3806	0.3806	0.3806	0.5380	0.3806	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
21	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3806	0.3806	0.3806	0.3806	0.3806	0.5380	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163
22	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.5380	0.3806	0.3806	0.3806	0.3806	0.3806
23	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3806	0.5380	0.3806	0.3806	0.3806	0.3806
24	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3806	0.3806	0.5380	0.3806	0.3806	0.3806
25	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3806	0.3806	0.3806	0.5380	0.3806	0.3806
26	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3806	0.3806	0.3806	0.3806	0.5380	0.3806
27	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3163	0.3806	0.3806	0.3806	0.3806	0.3806	0.5380

Estimated V Correlation Matrix for PersonID 101
Row	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13	Col14	Col15	Col16	Col17	Col18	Col19	Col20	Col21	Col22	Col23	Col24	Col25	Col26	Col27
1	1.0000	0.7075	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
2	0.7075	1.0000	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
3	0.7075	0.7075	1.0000	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
4	0.5879	0.5879	0.5879	1.0000	0.7075	0.7075	0.7075	0.7075	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
5	0.5879	0.5879	0.5879	0.7075	1.0000	0.7075	0.7075	0.7075	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
6	0.5879	0.5879	0.5879	0.7075	0.7075	1.0000	0.7075	0.7075	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
7	0.5879	0.5879	0.5879	0.7075	0.7075	0.7075	1.0000	0.7075	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
8	0.5879	0.5879	0.5879	0.7075	0.7075	0.7075	0.7075	1.0000	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
9	0.5879	0.5879	0.5879	0.7075	0.7075	0.7075	0.7075	0.7075	1.0000	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
10	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	1.0000	0.7075	0.7075	0.7075	0.7075	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
11	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.7075	1.0000	0.7075	0.7075	0.7075	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
12	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.7075	0.7075	1.0000	0.7075	0.7075	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
13	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.7075	0.7075	0.7075	1.0000	0.7075	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
14	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.7075	0.7075	0.7075	0.7075	1.0000	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
15	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.7075	0.7075	0.7075	0.7075	0.7075	1.0000	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
16	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	1.0000	0.7075	0.7075	0.7075	0.7075	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
17	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.7075	1.0000	0.7075	0.7075	0.7075	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
18	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.7075	0.7075	1.0000	0.7075	0.7075	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
19	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.7075	0.7075	0.7075	1.0000	0.7075	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
20	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.7075	0.7075	0.7075	0.7075	1.0000	0.7075	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
21	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.7075	0.7075	0.7075	0.7075	0.7075	1.0000	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879
22	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	1.0000	0.7075	0.7075	0.7075	0.7075	0.7075
23	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.7075	1.0000	0.7075	0.7075	0.7075	0.7075
24	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.7075	0.7075	1.0000	0.7075	0.7075	0.7075
25	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.7075	0.7075	0.7075	1.0000	0.7075	0.7075
26	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.7075	0.7075	0.7075	0.7075	1.0000	0.7075
27	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.5879	0.7075	0.7075	0.7075	0.7075	0.7075	1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr > Z
UN(1,1)	PersonID	0.3163	0.04661	6.79	<.0001
UN(1,1)	PersonID*burst	0.06433	0.006897	9.33	<.0001
Residual		0.1574	0.004657	33.79	<.0001

Fit Statistics
-2 Log Likelihood	3577.0
AIC (Smaller is Better)	3585.0
AICC (Smaller is Better)	3585.0
BIC (Smaller is Better)	3595.7

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
2	2503.39	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
3577.0	4	3585.0	3585.0	3589.3	3595.7	3599.7

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	2.5431	0.05623	107	45.23	<.0001	0.05	2.4317	2.6546

Likelihood Ratio Test for FitEmpty2P vs. FitEmpty3P

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitEmpty2P	3974.7	3	3980.7	3993.1	.	.	.
FitEmpty3P	3577.0	4	3585.0	3595.7	397.760	1	0

Eq 10b.6: Saturated Means for Burst by Session

Three-Level Model for the Variance for Symptoms

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	symptoms
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	3
Columns in X	42
Columns in Z per Subject	6
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2752
Number of Observations Not Used	0

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	9693.71198986
1	3	7385.06276103	0.00037463
2	1	7384.60392594	0.00000267
3	1	7384.60079915	0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr > Z
UN(1,1)	PersonID	1.1093	0.1718	6.46	<.0001
UN(1,1)	PersonID*burst	0.3739	0.03605	10.37	<.0001
Residual		0.6031	0.01783	33.83	<.0001

Fit Statistics
-2 Log Likelihood	7384.6
AIC (Smaller is Better)	7450.6
AICC (Smaller is Better)	7451.4
BIC (Smaller is Better)	7539.1

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
2	2309.11	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
7384.6	33	7450.6	7451.4	7486.5	7539.1	7572.1

Solution for Fixed Effects
Effect	burst: Measurement Burst (1-5)	session: Within-Burst Session (1-6)	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept			1.7637	0.1536	403	11.49	<.0001	0.05	1.4618	2.0656
session		1	0.2597	0.1252	2289	2.08	0.0381	0.05	0.01431	0.5052
session		2	-139E-17	0.1252	2289	-0.00	1.0000	0.05	-0.2454	0.2454
session		3	0.1169	0.1252	2289	0.93	0.3505	0.05	-0.1285	0.3623
session		4	0.07792	0.1252	2289	0.62	0.5336	0.05	-0.1675	0.3234
session		5	0.09091	0.1252	2289	0.73	0.4677	0.05	-0.1545	0.3363
session		6	0	.	.	.	.	.	.	.
burst	1		-0.4816	0.1501	1250	-3.21	0.0014	0.05	-0.7761	-0.1871
burst	2		-0.1254	0.1528	1248	-0.82	0.4119	0.05	-0.4253	0.1744
burst	3		-0.08550	0.1533	1248	-0.56	0.5772	0.05	-0.3863	0.2153
burst	4		-0.2532	0.1557	1247	-1.63	0.1041	0.05	-0.5587	0.05219
burst	5		0	.	.	.	.	.	.	.
burst*session	1	1	0.02150	0.1648	2291	0.13	0.8962	0.05	-0.3016	0.3446
burst*session	1	2	0.04196	0.1644	2290	0.26	0.7985	0.05	-0.2804	0.3643
burst*session	1	3	0.04488	0.1648	2291	0.27	0.7854	0.05	-0.2782	0.3680
burst*session	1	4	-0.07014	0.1647	2290	-0.43	0.6702	0.05	-0.3931	0.2528
burst*session	1	5	-0.05300	0.1646	2291	-0.32	0.7475	0.05	-0.3757	0.2697
burst*session	1	6	0	.	.	.	.	.	.	.
burst*session	2	1	0.1158	0.1683	2291	0.69	0.4912	0.05	-0.2141	0.4458
burst*session	2	2	0.08392	0.1683	2291	0.50	0.6180	0.05	-0.2461	0.4139
burst*session	2	3	-0.04320	0.1684	2289	-0.26	0.7976	0.05	-0.3734	0.2870
burst*session	2	4	-0.06740	0.1684	2289	-0.40	0.6890	0.05	-0.3976	0.2628
burst*session	2	5	-0.01722	0.1684	2289	-0.10	0.9185	0.05	-0.3475	0.3130
burst*session	2	6	0	.	.	.	.	.	.	.
burst*session	3	1	0.4287	0.1691	2292	2.54	0.0113	0.05	0.09708	0.7603
burst*session	3	2	0.4086	0.1692	2289	2.41	0.0158	0.05	0.07678	0.7404
burst*session	3	3	0.1842	0.1692	2289	1.09	0.2765	0.05	-0.1476	0.5160
burst*session	3	4	0.07262	0.1692	2289	0.43	0.6679	0.05	-0.2592	0.4044
burst*session	3	5	-0.05865	0.1692	2289	-0.35	0.7289	0.05	-0.3905	0.2732
burst*session	3	6	0	.	.	.	.	.	.	.
burst*session	4	1	0.2575	0.1718	2289	1.50	0.1341	0.05	-0.07947	0.5945
burst*session	4	2	0.3218	0.1718	2289	1.87	0.0612	0.05	-0.01513	0.6588
burst*session	4	3	0.1219	0.1721	2290	0.71	0.4790	0.05	-0.2156	0.4594
burst*session	4	4	0.2669	0.1718	2289	1.55	0.1205	0.05	-0.07006	0.6039
burst*session	4	5	0.1390	0.1718	2289	0.81	0.4187	0.05	-0.1980	0.4759
burst*session	4	6	0	.	.	.	.	.	.	.
burst*session	5	1	0	.	.	.	.	.	.	.
burst*session	5	2	0	.	.	.	.	.	.	.
burst*session	5	3	0	.	.	.	.	.	.	.
burst*session	5	4	0	.	.	.	.	.	.	.
burst*session	5	5	0	.	.	.	.	.	.	.
burst*session	5	6	0	.	.	.	.	.	.	.

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
session	5	2291	76.76	15.35	<.0001	<.0001
burst	4	355	39.10	9.78	<.0001	<.0001
burst*session	20	2291	26.44	1.32	0.1518	0.1533

Least Squares Means
Effect	burst: Measurement Burst (1-5)	session: Within-Burst Session (1-6)	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
session		1	1.9990	0.1123	125	17.80	<.0001	0.05	1.7767	2.2213
session		2	1.7458	0.1123	125	15.54	<.0001	0.05	1.5235	1.9682
session		3	1.7530	0.1124	125	15.60	<.0001	0.05	1.5306	1.9754
session		4	1.6929	0.1124	125	15.06	<.0001	0.05	1.4705	1.9153
session		5	1.6675	0.1124	125	14.84	<.0001	0.05	1.4451	1.8899
session		6	1.5746	0.1124	125	14.01	<.0001	0.05	1.3521	1.7970
burst	1		1.3706	0.1212	168	11.31	<.0001	0.05	1.1313	1.6098
burst	2		1.7412	0.1246	183	13.98	<.0001	0.05	1.4954	1.9869
burst	3		1.9417	0.1253	186	15.50	<.0001	0.05	1.6946	2.1888
burst	4		1.7859	0.1272	196	14.04	<.0001	0.05	1.5350	2.0367
burst	5		1.8546	0.1306	213	14.20	<.0001	0.05	1.5972	2.1120
burst*session	1	1	1.5634	0.1394	293	11.21	<.0001	0.05	1.2889	1.8378
burst*session	1	2	1.3241	0.1390	289	9.53	<.0001	0.05	1.0505	1.5976
burst*session	1	3	1.4439	0.1394	292	10.35	<.0001	0.05	1.1694	1.7183
burst*session	1	4	1.2899	0.1394	292	9.25	<.0001	0.05	1.0154	1.5643
burst*session	1	5	1.3200	0.1392	291	9.48	<.0001	0.05	1.0460	1.5940
burst*session	1	6	1.2821	0.1397	294	9.18	<.0001	0.05	1.0072	1.5570
burst*session	2	1	2.0139	0.1440	324	13.99	<.0001	0.05	1.7306	2.2971
burst*session	2	2	1.7222	0.1440	324	11.96	<.0001	0.05	1.4389	2.0055
burst*session	2	3	1.7120	0.1443	327	11.86	<.0001	0.05	1.4281	1.9958
burst*session	2	4	1.6488	0.1443	327	11.43	<.0001	0.05	1.3649	1.9327
burst*session	2	5	1.7120	0.1443	327	11.86	<.0001	0.05	1.4281	1.9958
burst*session	2	6	1.6383	0.1443	327	11.35	<.0001	0.05	1.3544	1.9221
burst*session	3	1	2.3667	0.1449	331	16.33	<.0001	0.05	2.0815	2.6518
burst*session	3	2	2.0868	0.1453	334	14.36	<.0001	0.05	1.8010	2.3726
burst*session	3	3	1.9793	0.1453	334	13.62	<.0001	0.05	1.6935	2.2651
burst*session	3	4	1.8287	0.1453	334	12.59	<.0001	0.05	1.5429	2.1146
burst*session	3	5	1.7105	0.1453	334	11.77	<.0001	0.05	1.4247	1.9963
burst*session	3	6	1.6782	0.1453	334	11.55	<.0001	0.05	1.3924	1.9640
burst*session	4	1	2.0277	0.1482	357	13.69	<.0001	0.05	1.7363	2.3191
burst*session	4	2	1.8323	0.1482	357	12.37	<.0001	0.05	1.5409	2.1237
burst*session	4	3	1.7492	0.1485	360	11.78	<.0001	0.05	1.4572	2.0412
burst*session	4	4	1.8553	0.1482	357	12.52	<.0001	0.05	1.5639	2.1467
burst*session	4	5	1.7404	0.1482	357	11.75	<.0001	0.05	1.4490	2.0317
burst*session	4	6	1.5105	0.1482	357	10.19	<.0001	0.05	1.2191	1.8018
burst*session	5	1	2.0235	0.1536	403	13.18	<.0001	0.05	1.7216	2.3253
burst*session	5	2	1.7637	0.1536	403	11.49	<.0001	0.05	1.4618	2.0656
burst*session	5	3	1.8806	0.1536	403	12.25	<.0001	0.05	1.5787	2.1825
burst*session	5	4	1.8416	0.1536	403	11.99	<.0001	0.05	1.5397	2.1435
burst*session	5	5	1.8546	0.1536	403	12.08	<.0001	0.05	1.5527	2.1565
burst*session	5	6	1.7637	0.1536	403	11.49	<.0001	0.05	1.4618	2.0656

Eq 10b.7: Piecewise Session Slopes by Observed Burst

Three-Level Model for the Variance for Symptoms

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	symptoms
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	3
Columns in X	18
Columns in Z per Subject	6
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2752
Number of Observations Not Used	0

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	9696.74368526
1	3	7394.54256328	0.00037830
2	1	7394.07718627	0.00000274
3	1	7394.07397029	0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr > Z
UN(1,1)	PersonID	1.1098	0.1719	6.46	<.0001
UN(1,1)	PersonID*burst	0.3735	0.03605	10.36	<.0001
Residual		0.6056	0.01790	33.83	<.0001

Fit Statistics
-2 Log Likelihood	7394.1
AIC (Smaller is Better)	7430.1
AICC (Smaller is Better)	7430.3
BIC (Smaller is Better)	7478.4

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
2	2302.67	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
7394.1	18	7430.1	7430.3	7449.6	7478.4	7496.4

Solution for Fixed Effects
Effect	burst: Measurement Burst (1-5)	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept		1.8262	0.1431	306	12.77	<.0001	0.05	1.5447	2.1077
slope12		-0.1974	0.1122	2289	-1.76	0.0786	0.05	-0.4174	0.02257
slope26		-0.00260	0.02804	2289	-0.09	0.9262	0.05	-0.05759	0.05240
burst	1	-0.4534	0.1306	797	-3.47	0.0005	0.05	-0.7096	-0.1971
burst	2	-0.1059	0.1329	796	-0.80	0.4259	0.05	-0.3668	0.1550
burst	3	0.2478	0.1335	798	1.86	0.0637	0.05	-0.01419	0.5098
burst	4	0.04223	0.1355	797	0.31	0.7555	0.05	-0.2238	0.3083
burst	5	0	.	.	.	.	.	.	.
slope12*burst	1	0.007045	0.1473	2290	0.05	0.9619	0.05	-0.2818	0.2959
slope12*burst	2	-0.09624	0.1506	2289	-0.64	0.5230	0.05	-0.3917	0.1992
slope12*burst	3	-0.09537	0.1515	2293	-0.63	0.5292	0.05	-0.3925	0.2018
slope12*burst	4	0.03801	0.1541	2289	0.25	0.8051	0.05	-0.2641	0.3401
slope12*burst	5	0	.	.	.	.	.	.	.
slope26*burst	1	-0.01793	0.03683	2290	-0.49	0.6263	0.05	-0.09015	0.05429
slope26*burst	2	-0.01419	0.03771	2290	-0.38	0.7067	0.05	-0.08814	0.05976
slope26*burst	3	-0.1060	0.03792	2289	-2.80	0.0052	0.05	-0.1804	-0.03165
slope26*burst	4	-0.06273	0.03852	2289	-1.63	0.1035	0.05	-0.1383	0.01280
slope26*burst	5	0	.	.	.	.	.	.	.

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
slope12	1	2291	24.09	24.09	<.0001	<.0001
slope26	1	2290	13.69	13.69	0.0002	0.0002
burst	4	802	35.27	8.82	<.0001	<.0001
slope12*burst	4	2292	1.48	0.37	0.8298	0.8298
slope26*burst	4	2290	11.37	2.84	0.0227	0.0230

Estimates
Label	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Session 2 at Burst 1	1.3728	0.1309	228	10.49	<.0001	0.05	1.1150	1.6307
Session 2 at Burst 2	1.7203	0.1351	253	12.73	<.0001	0.05	1.4542	1.9864
Session 2 at Burst 3	2.0740	0.1361	259	15.24	<.0001	0.05	1.8059	2.3421
Session 2 at Burst 4	1.8684	0.1386	275	13.48	<.0001	0.05	1.5956	2.1413
Session 2 at Burst 5	1.8262	0.1431	306	12.77	<.0001	0.05	1.5447	2.1077
Slope12 at Burst 1	-0.1904	0.09548	2291	-1.99	0.0463	0.05	-0.3776	-0.00311
Slope12 at Burst 2	-0.2936	0.1006	2290	-2.92	0.0035	0.05	-0.4908	-0.09645
Slope12 at Burst 3	-0.2928	0.1019	2298	-2.87	0.0041	0.05	-0.4926	-0.09295
Slope12 at Burst 4	-0.1594	0.1056	2289	-1.51	0.1313	0.05	-0.3665	0.04769
Slope12 at Burst 5	-0.1974	0.1122	2289	-1.76	0.0786	0.05	-0.4174	0.02257
Slope26 at Burst 1	-0.02053	0.02387	2291	-0.86	0.3899	0.05	-0.06734	0.02628
Slope26 at Burst 2	-0.01679	0.02521	2292	-0.67	0.5055	0.05	-0.06623	0.03265
Slope26 at Burst 3	-0.1086	0.02552	2289	-4.26	<.0001	0.05	-0.1586	-0.05856
Slope26 at Burst 4	-0.06532	0.02640	2289	-2.47	0.0134	0.05	-0.1171	-0.01355
Slope26 at Burst 5	-0.00260	0.02804	2289	-0.09	0.9262	0.05	-0.05759	0.05240

Eq 10b.8: Piecewise Session Slopes by Quadratic Burst

Three-Level Model for the Variance for Symptoms

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	symptoms
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	3
Columns in X	9
Columns in Z per Subject	6
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2752
Number of Observations Not Used	0

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	9705.38531542
1	3	7405.47172223	0.00033182
2	1	7405.06280803	0.00000211
3	1	7405.06032088	0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr > Z
UN(1,1)	PersonID	1.1070	0.1717	6.45	<.0001
UN(1,1)	PersonID*burst	0.3792	0.03651	10.39	<.0001
Residual		0.6073	0.01795	33.83	<.0001

Fit Statistics
-2 Log Likelihood	7405.1
AIC (Smaller is Better)	7429.1
AICC (Smaller is Better)	7429.2
BIC (Smaller is Better)	7461.2

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
2	2300.32	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
7405.1	12	7429.1	7429.2	7442.1	7461.2	7473.2

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	1.3677	0.1284	213	10.65	<.0001	0.05	1.1146	1.6209
burst1	0.4929	0.09882	802	4.99	<.0001	0.05	0.2989	0.6868
burst1*burst1	-0.09701	0.02433	799	-3.99	<.0001	0.05	-0.1448	-0.04925
slope12	-0.2096	0.09068	2291	-2.31	0.0209	0.05	-0.3874	-0.03178
slope26	-0.00581	0.02268	2291	-0.26	0.7978	0.05	-0.05028	0.03866
burst1*slope12	-0.07014	0.1120	2292	-0.63	0.5311	0.05	-0.2897	0.1494
burst1*slope26	-0.07120	0.02801	2290	-2.54	0.0111	0.05	-0.1261	-0.01627
burst1burst1slope12	0.02062	0.02760	2292	0.75	0.4550	0.05	-0.03349	0.07473
burst1burst1slope26	0.01750	0.006904	2290	2.53	0.0113	0.05	0.003959	0.03104

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	802	24.87	24.87	<.0001	<.0001
burst1*burst1	1	799	15.89	15.89	<.0001	<.0001
slope12	1	2291	5.34	5.34	0.0208	0.0209
slope26	1	2291	0.07	0.07	0.7978	0.7978
burst1*slope12	1	2292	0.39	0.39	0.5311	0.5311
burst1*slope26	1	2290	6.46	6.46	0.0110	0.0111
burst1burst1slope12	1	2292	0.56	0.56	0.4549	0.4550
burst1burst1slope26	1	2290	6.42	6.42	0.0113	0.0113

Estimates
Label	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Slope12 at Burst 1	-0.2096	0.09068	2291	-2.31	0.0209	0.05	-0.3874	-0.03178
Slope12 at Burst 2	-0.2591	0.06174	2293	-4.20	<.0001	0.05	-0.3802	-0.1381
Slope12 at Burst 3	-0.2674	0.07151	2294	-3.74	0.0002	0.05	-0.4076	-0.1272
Slope12 at Burst 4	-0.2344	0.06392	2292	-3.67	0.0003	0.05	-0.3598	-0.1091
Slope12 at Burst 5	-0.1602	0.1047	2289	-1.53	0.1261	0.05	-0.3655	0.04508
Slope26 at Burst 1	-0.00581	0.02268	2291	-0.26	0.7978	0.05	-0.05028	0.03866
Slope26 at Burst 2	-0.05951	0.01546	2290	-3.85	0.0001	0.05	-0.08983	-0.02920
Slope26 at Burst 3	-0.07822	0.01790	2290	-4.37	<.0001	0.05	-0.1133	-0.04311
Slope26 at Burst 4	-0.06193	0.01599	2289	-3.87	0.0001	0.05	-0.09329	-0.03057
Slope26 at Burst 5	-0.01064	0.02618	2289	-0.41	0.6844	0.05	-0.06197	0.04069

Likelihood Ratio Test for FitPiecebyQuadBurstS vs. FitPiecebyBurstMeansS

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitPiecebyQuadBurstS	7405.1	12	7429.1	7461.2	.	.	.
FitPiecebyBurstMeansS	7394.1	18	7430.1	7478.4	10.9864	6	0.088799

Eq 10b.9: Piecewise Session Slopes (Slope26 by Quadratic Burst Only)

Three-Level Model for the Variance for Symptoms

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	symptoms
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	3
Columns in X	7
Columns in Z per Subject	6
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2752
Number of Observations Not Used	0

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	9705.66306286
1	3	7406.11841955	0.00032981
2	1	7405.71193156	0.00000208
3	1	7405.70947441	0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr > Z
UN(1,1)	PersonID	1.1071	0.1717	6.45	<.0001
UN(1,1)	PersonID*burst	0.3792	0.03651	10.39	<.0001
Residual		0.6075	0.01796	33.83	<.0001

Fit Statistics
-2 Log Likelihood	7405.7
AIC (Smaller is Better)	7425.7
AICC (Smaller is Better)	7425.8
BIC (Smaller is Better)	7452.5

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
2	2299.95	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
7405.7	10	7425.7	7425.8	7436.6	7452.5	7462.5

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	1.3609	0.1251	192	10.88	<.0001	0.05	1.1142	1.6076
burst1	0.5192	0.08947	558	5.80	<.0001	0.05	0.3435	0.6950
burst1*burst1	-0.1048	0.02202	554	-4.76	<.0001	0.05	-0.1480	-0.06151
slope12	-0.2281	0.04600	2291	-4.96	<.0001	0.05	-0.3183	-0.1379
slope26	-0.00351	0.02049	2291	-0.17	0.8640	0.05	-0.04369	0.03667
burst1*slope26	-0.07997	0.02428	2291	-3.29	0.0010	0.05	-0.1276	-0.03236
burst1burst1slope26	0.02008	0.005982	2291	3.36	0.0008	0.05	0.008345	0.03181

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	558	33.68	33.68	<.0001	<.0001
burst1*burst1	1	554	22.63	22.63	<.0001	<.0001
slope12	1	2291	24.58	24.58	<.0001	<.0001
slope26	1	2291	0.03	0.03	0.8640	0.8640
burst1*slope26	1	2291	10.85	10.85	0.0010	0.0010
burst1burst1slope26	1	2291	11.26	11.26	0.0008	0.0008

Estimates
Label	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Slope26 at Burst 1	-0.00351	0.02049	2291	-0.17	0.8640	0.05	-0.04369	0.03667
Slope26 at Burst 2	-0.06340	0.01458	2291	-4.35	<.0001	0.05	-0.09199	-0.03482
Slope26 at Burst 3	-0.08314	0.01654	2291	-5.03	<.0001	0.05	-0.1156	-0.05070
Slope26 at Burst 4	-0.06272	0.01500	2290	-4.18	<.0001	0.05	-0.09214	-0.03331
Slope26 at Burst 5	-0.00216	0.02339	2289	-0.09	0.9266	0.05	-0.04802	0.04371

Likelihood Ratio Test for FitPieceQuadBurst26S vs. FitPiecebyBurstMeansS

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitPieceQuadBurst26S	7405.7	10	7425.7	7452.5	.	.	.
FitPiecebyBurstMeansS	7394.1	18	7430.1	7478.4	11.6355	8	0.16822

Likelihood Ratio Test for FitPieceQuadBurst26S vs. FitSatAllS

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitPieceQuadBurst26S	7405.7	10	7425.7	7452.5	.	.	.
FitSatAllS	7384.6	33	7450.6	7539.1	21.1087	23	0.57445

Ch 10b: Piecewise Session Slopes (Slope26 by Quadratic Burst Only)

Add Random Linear Burst Slope across Persons for Symptoms

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	symptoms
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	5
Columns in X	7
Columns in Z per Subject	7
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2752
Number of Observations Not Used	0

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	9705.66306286
1	3	7399.75933328	0.00068314
2	1	7398.90447288	0.00000869
3	1	7398.89420643	0.00000000

Convergence criteria met.

Estimated G Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7
1	Intercept	101		0.9360	0.04410
2	burst1	101		0.04410	0.01249
3	Intercept	101	1			0.3490
4	Intercept	101	2				0.3490
5	Intercept	101	3					0.3490
6	Intercept	101	4						0.3490
7	Intercept	101	5							0.3490

Estimated G Correlation Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7
1	Intercept	101		1.0000	0.4078
2	burst1	101		0.4078	1.0000
3	Intercept	101	1			1.0000
4	Intercept	101	2				1.0000
5	Intercept	101	3					1.0000
6	Intercept	101	4						1.0000
7	Intercept	101	5							1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr Z
UN(1,1)	PersonID	0.9360	0.1728	5.42	<.0001
UN(2,1)	PersonID	0.04410	0.03220	1.37	0.1708
UN(2,2)	PersonID	0.01249	0.01026	1.22	0.1116
UN(1,1)	PersonID*burst	0.3490	0.03994	8.74	<.0001
Residual		0.6075	0.01796	33.83	<.0001

Fit Statistics
-2 Log Likelihood	7398.9
AIC (Smaller is Better)	7422.9
AICC (Smaller is Better)	7423.0
BIC (Smaller is Better)	7455.1

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
4	2306.77	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
7398.9	12	7422.9	7423.0	7435.9	7455.1	7467.1

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	1.3600	0.1175	152	11.57	<.0001	0.05	1.1278	1.5921
burst1	0.5182	0.08812	507	5.88	<.0001	0.05	0.3451	0.6914
burst1*burst1	-0.1033	0.02155	453	-4.80	<.0001	0.05	-0.1457	-0.06099
slope12	-0.2279	0.04600	2291	-4.95	<.0001	0.05	-0.3181	-0.1377
slope26	-0.00370	0.02049	2292	-0.18	0.8567	0.05	-0.04388	0.03648
burst1*slope26	-0.07980	0.02428	2291	-3.29	0.0010	0.05	-0.1274	-0.03219
burst1burst1slope26	0.02004	0.005982	2291	3.35	0.0008	0.05	0.008313	0.03178

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	507	34.58	34.58	<.0001	<.0001
burst1*burst1	1	453	23.00	23.00	<.0001	<.0001
slope12	1	2291	24.54	24.54	<.0001	<.0001
slope26	1	2292	0.03	0.03	0.8567	0.8567
burst1*slope26	1	2291	10.80	10.80	0.0010	0.0010
burst1burst1slope26	1	2291	11.23	11.23	0.0008	0.0008

Likelihood Ratio Test for FitPieceQuadBurst26S vs. FitRandBurstLin3S

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitPieceQuadBurst26S	7405.7	10	7425.7	7452.5	.	.	.
FitRandBurstLin3S	7398.9	12	7422.9	7455.1	6.81527	2	0.033119

Ch 10b: Piecewise Session Slopes (Slope26 by Quadratic Burst Only)

Add Random Quadratic Burst Slope across Persons for Symptoms

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	symptoms
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	8
Columns in X	7
Columns in Z per Subject	8
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2752
Number of Observations Not Used	0

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	9705.66306286
1	2	7574.17794827	287.94068140
2	1	7490.27037965	1778.4142214
3	1	7431.40704604	0.21304954
4	3	7423.36143766	.
5	3	7408.03784592	.
6	1	7398.64520195	.
7	1	7396.17736001	0.00013906
8	1	7396.00500376	0.00000139
9	1	7396.00336031	0.00000000

Convergence criteria met.

Estimated G Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8
1	Intercept	101		0.8704	0.1215	-0.02301
2	burst1	101		0.1215	0.1105	-0.02292
3	burst1*burst1	101		-0.02301	-0.02292	0.005473
4	Intercept	101	1				0.3239
5	Intercept	101	2					0.3239
6	Intercept	101	3						0.3239
7	Intercept	101	4							0.3239
8	Intercept	101	5								0.3239

Estimated G Correlation Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8
1	Intercept	101		1.0000	0.3918	-0.3334
2	burst1	101		0.3918	1.0000	-0.9322
3	burst1*burst1	101		-0.3334	-0.9322	1.0000
4	Intercept	101	1				1.0000
5	Intercept	101	2					1.0000
6	Intercept	101	3						1.0000
7	Intercept	101	4							1.0000
8	Intercept	101	5								1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr Z
UN(1,1)	PersonID	0.8704	0.1776	4.90	<.0001
UN(2,1)	PersonID	0.1215	0.1050	1.16	0.2474
UN(2,2)	PersonID	0.1105	0.1175	0.94	0.1737
UN(3,1)	PersonID	-0.02301	0.02512	-0.92	0.3595
UN(3,2)	PersonID	-0.02292	0.02781	-0.82	0.4098
UN(3,3)	PersonID	0.005473	0.006928	0.79	0.2148
UN(1,1)	PersonID*burst	0.3239	0.04622	7.01	<.0001
Residual		0.6074	0.01795	33.83	<.0001

Fit Statistics
-2 Log Likelihood	7396.0
AIC (Smaller is Better)	7426.0
AICC (Smaller is Better)	7426.2
BIC (Smaller is Better)	7466.2

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
7	2309.66	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
7396.0	15	7426.0	7426.2	7442.3	7466.2	7481.2

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	1.3596	0.1140	132	11.93	<.0001	0.05	1.1341	1.5850
burst1	0.5269	0.09198	141	5.73	<.0001	0.05	0.3451	0.7087
burst1*burst1	-0.1060	0.02243	132	-4.73	<.0001	0.05	-0.1504	-0.06165
slope12	-0.2276	0.04600	2292	-4.95	<.0001	0.05	-0.3178	-0.1374
slope26	-0.00379	0.02049	2292	-0.19	0.8531	0.05	-0.04397	0.03638
burst1*slope26	-0.07967	0.02428	2291	-3.28	0.0010	0.05	-0.1273	-0.03206
burst1burst1slope26	0.02001	0.005982	2291	3.35	0.0008	0.05	0.008283	0.03174

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	141	32.82	32.82	<.0001	<.0001
burst1*burst1	1	132	22.35	22.35	<.0001	<.0001
slope12	1	2292	24.48	24.48	<.0001	<.0001
slope26	1	2292	0.03	0.03	0.8531	0.8531
burst1*slope26	1	2291	10.77	10.77	0.0010	0.0010
burst1burst1slope26	1	2291	11.19	11.19	0.0008	0.0008

Likelihood Ratio Test for FitRandBurstLin3S vs. FitRandBurstQuad3S

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitRandBurstLin3S	7398.9	12	7422.9	7455.1	.	.	.
FitRandBurstQuad3S	7396.0	15	7426.0	7466.2	2.89085	3	0.40876

Ch 10b: Piecewise Session Slopes (Slope26 by Quadratic Burst Only)

Add Random Linear Slope12 Across Bursts for Symptoms

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	symptoms
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	7
Columns in X	7
Columns in Z per Subject	12
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2752
Number of Observations Not Used	0

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	9705.66306286
1	3	7380.46588300	0.00080433
2	1	7379.46174934	0.00001248
3	1	7379.44709608	0.00000000

Convergence criteria met.

Estimated G Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12
1	Intercept	101		0.9392	0.04365
2	burst1	101		0.04365	0.01201
3	Intercept	101	1			0.3721	0.06849
4	slope12	101	1			0.06849	0.2482
5	Intercept	101	2					0.3721	0.06849
6	slope12	101	2					0.06849	0.2482
7	Intercept	101	3							0.3721	0.06849
8	slope12	101	3							0.06849	0.2482
9	Intercept	101	4									0.3721	0.06849
10	slope12	101	4									0.06849	0.2482
11	Intercept	101	5											0.3721	0.06849
12	slope12	101	5											0.06849	0.2482

Estimated G Correlation Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12
1	Intercept	101		1.0000	0.4110
2	burst1	101		0.4110	1.0000
3	Intercept	101	1			1.0000	0.2254
4	slope12	101	1			0.2254	1.0000
5	Intercept	101	2					1.0000	0.2254
6	slope12	101	2					0.2254	1.0000
7	Intercept	101	3							1.0000	0.2254
8	slope12	101	3							0.2254	1.0000
9	Intercept	101	4									1.0000	0.2254
10	slope12	101	4									0.2254	1.0000
11	Intercept	101	5											1.0000	0.2254
12	slope12	101	5											0.2254	1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr Z
UN(1,1)	PersonID	0.9392	0.1732	5.42	<.0001
UN(2,1)	PersonID	0.04365	0.03213	1.36	0.1743
UN(2,2)	PersonID	0.01201	0.01020	1.18	0.1195
UN(1,1)	PersonID*burst	0.3721	0.04259	8.74	<.0001
UN(2,1)	PersonID*burst	0.06849	0.03729	1.84	0.0663
UN(2,2)	PersonID*burst	0.2482	0.06530	3.80	<.0001
Residual		0.5661	0.01871	30.26	<.0001

Fit Statistics
-2 Log Likelihood	7379.4
AIC (Smaller is Better)	7407.4
AICC (Smaller is Better)	7407.6
BIC (Smaller is Better)	7445.0

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
6	2326.22	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
7379.4	14	7407.4	7407.6	7422.7	7445.0	7459.0

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	1.3603	0.1174	151	11.59	<.0001	0.05	1.1284	1.5922
burst1	0.5162	0.08741	457	5.91	<.0001	0.05	0.3444	0.6880
burst1*burst1	-0.1029	0.02138	412	-4.81	<.0001	0.05	-0.1449	-0.06084
slope12	-0.2283	0.05012	699	-4.55	<.0001	0.05	-0.3267	-0.1299
slope26	-0.00417	0.02026	2235	-0.21	0.8370	0.05	-0.04389	0.03555
burst1*slope26	-0.07805	0.02426	2291	-3.22	0.0013	0.05	-0.1256	-0.03048
burst1burst1slope26	0.01953	0.005978	2291	3.27	0.0011	0.05	0.007805	0.03125

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	457	34.87	34.87	<.0001	<.0001
burst1*burst1	1	412	23.15	23.15	<.0001	<.0001
slope12	1	699	20.74	20.74	<.0001	<.0001
slope26	1	2235	0.04	0.04	0.8369	0.8370
burst1*slope26	1	2291	10.35	10.35	0.0013	0.0013
burst1burst1slope26	1	2291	10.67	10.67	0.0011	0.0011

Likelihood Ratio Test for FitRandBurstLin3S vs. FitRandSlope12at2S

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitRandBurstLin3S	7398.9	12	7422.9	7455.1	.	.	.
FitRandSlope12at2S	7379.4	14	7407.4	7445.0	19.4471	2	.000059857

Ch 10b: Piecewise Session Slopes (Slope26 by Quadratic Burst Only)

Add Random Linear Slope12 Across Persons for Symptoms

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	symptoms
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	10
Columns in X	7
Columns in Z per Subject	13
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2752
Number of Observations Not Used	0

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	9705.66306286
1	2	7374.94641336	0.00079840
2	1	7373.95088356	0.00001319
3	1	7373.93541265	0.00000001

Convergence criteria met.

Estimated G Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13
1	Intercept	101		0.9173	0.04832	-0.04793
2	burst1	101		0.04832	0.01197	0.01998
3	slope12	101		-0.04793	0.01998	0.04799
4	Intercept	101	1				0.3723	0.06390
5	slope12	101	1				0.06390	0.1996
6	Intercept	101	2						0.3723	0.06390
7	slope12	101	2						0.06390	0.1996
8	Intercept	101	3								0.3723	0.06390
9	slope12	101	3								0.06390	0.1996
10	Intercept	101	4										0.3723	0.06390
11	slope12	101	4										0.06390	0.1996
12	Intercept	101	5												0.3723	0.06390
13	slope12	101	5												0.06390	0.1996

Estimated G Correlation Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13
1	Intercept	101		1.0000	0.4611	-0.2285
2	burst1	101		0.4611	1.0000	0.8337
3	slope12	101		-0.2285	0.8337	1.0000
4	Intercept	101	1				1.0000	0.2344
5	slope12	101	1				0.2344	1.0000
6	Intercept	101	2						1.0000	0.2344
7	slope12	101	2						0.2344	1.0000
8	Intercept	101	3								1.0000	0.2344
9	slope12	101	3								0.2344	1.0000
10	Intercept	101	4										1.0000	0.2344
11	slope12	101	4										0.2344	1.0000
12	Intercept	101	5												1.0000	0.2344
13	slope12	101	5												0.2344	1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr Z
UN(1,1)	PersonID	0.9173	0.1715	5.35	<.0001
UN(2,1)	PersonID	0.04832	0.03187	1.52	0.1294
UN(2,2)	PersonID	0.01197	0.01020	1.17	0.1201
UN(3,1)	PersonID	-0.04793	0.05691	-0.84	0.3997
UN(3,2)	PersonID	0.01998	0.01230	1.62	0.1043
UN(3,3)	PersonID	0.04799	0.03514	1.37	0.0860
UN(1,1)	PersonID*burst	0.3723	0.04272	8.71	<.0001
UN(2,1)	PersonID*burst	0.06390	0.03637	1.76	0.0789
UN(2,2)	PersonID*burst	0.1996	0.06888	2.90	0.0019
Residual		0.5662	0.01871	30.26	<.0001

Fit Statistics
-2 Log Likelihood	7373.9
AIC (Smaller is Better)	7407.9
AICC (Smaller is Better)	7408.2
BIC (Smaller is Better)	7453.5

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
9	2331.73	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
7373.9	17	7407.9	7408.2	7426.4	7453.5	7470.5

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	1.3614	0.1164	149	11.69	<.0001	0.05	1.1313	1.5915
burst1	0.5148	0.08718	456	5.91	<.0001	0.05	0.3435	0.6862
burst1*burst1	-0.1024	0.02131	410	-4.80	<.0001	0.05	-0.1443	-0.06049
slope12	-0.2285	0.05367	160	-4.26	<.0001	0.05	-0.3345	-0.1225
slope26	-0.00445	0.02019	2201	-0.22	0.8255	0.05	-0.04404	0.03514
burst1*slope26	-0.07794	0.02414	2193	-3.23	0.0013	0.05	-0.1253	-0.03060
burst1burst1slope26	0.01954	0.005948	2192	3.28	0.0010	0.05	0.007874	0.03120

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	456	34.87	34.87	<.0001	<.0001
burst1*burst1	1	410	23.08	23.08	<.0001	<.0001
slope12	1	160	18.12	18.12	<.0001	<.0001
slope26	1	2201	0.05	0.05	0.8255	0.8255
burst1*slope26	1	2193	10.42	10.42	0.0012	0.0013
burst1burst1slope26	1	2192	10.79	10.79	0.0010	0.0010

Likelihood Ratio Test for FitRandSlope12at2S vs. FitRandSlope12at23S

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitRandSlope12at2S	7379.4	14	7407.4	7445.0	.	.	.
FitRandSlope12at23S	7373.9	17	7407.9	7453.5	5.51168	3	0.13794

Eq 10b.10: Piecewise Session Slopes (Slope26 by Quadratic Burst Only)

Add Random Linear Slope26 Across Bursts for Symptoms

The Mixed Procedure

Model Information
Data Set	WORK.PLOTMEANS
Dependent Variable	symptoms
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	10
Columns in X	7
Columns in Z per Subject	17
Subjects	109
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2782
Number of Observations Used	2752
Number of Observations Not Used	30

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	9705.66306286
1	3	7355.62051692	0.00090330
2	1	7354.49935521	0.00001630
3	1	7354.48039375	0.00000001

Convergence criteria met.

Estimated G Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13	Col14	Col15	Col16	Col17
1	Intercept	-99		0.9383	0.04312
2	burst1	-99		0.04312	0.01231
3	Intercept	-99	1			0.5124	0.09929	-0.04592
4	slope12	-99	1			0.09929	0.2010	0.008945
5	slope26	-99	1			-0.04592	0.008945	0.01198
6	Intercept	-99	2						0.5124	0.09929	-0.04592
7	slope12	-99	2						0.09929	0.2010	0.008945
8	slope26	-99	2						-0.04592	0.008945	0.01198
9	Intercept	-99	3									0.5124	0.09929	-0.04592
10	slope12	-99	3									0.09929	0.2010	0.008945
11	slope26	-99	3									-0.04592	0.008945	0.01198
12	Intercept	-99	4												0.5124	0.09929	-0.04592
13	slope12	-99	4												0.09929	0.2010	0.008945
14	slope26	-99	4												-0.04592	0.008945	0.01198
15	Intercept	-99	5															0.5124	0.09929	-0.04592
16	slope12	-99	5															0.09929	0.2010	0.008945
17	slope26	-99	5															-0.04592	0.008945	0.01198

Estimated G Correlation Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13	Col14	Col15	Col16	Col17
1	Intercept	-99		1.0000	0.4012
2	burst1	-99		0.4012	1.0000
3	Intercept	-99	1			1.0000	0.3094	-0.5861
4	slope12	-99	1			0.3094	1.0000	0.1823
5	slope26	-99	1			-0.5861	0.1823	1.0000
6	Intercept	-99	2						1.0000	0.3094	-0.5861
7	slope12	-99	2						0.3094	1.0000	0.1823
8	slope26	-99	2						-0.5861	0.1823	1.0000
9	Intercept	-99	3									1.0000	0.3094	-0.5861
10	slope12	-99	3									0.3094	1.0000	0.1823
11	slope26	-99	3									-0.5861	0.1823	1.0000
12	Intercept	-99	4												1.0000	0.3094	-0.5861
13	slope12	-99	4												0.3094	1.0000	0.1823
14	slope26	-99	4												-0.5861	0.1823	1.0000
15	Intercept	-99	5															1.0000	0.3094	-0.5861
16	slope12	-99	5															0.3094	1.0000	0.1823
17	slope26	-99	5															-0.5861	0.1823	1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr Z
UN(1,1)	PersonID	0.9383	0.1721	5.45	<.0001
UN(2,1)	PersonID	0.04312	0.03172	1.36	0.1741
UN(2,2)	PersonID	0.01231	0.01004	1.23	0.1100
UN(1,1)	PersonID*burst	0.5124	0.06579	7.79	<.0001
UN(2,1)	PersonID*burst	0.09929	0.05291	1.88	0.0606
UN(2,2)	PersonID*burst	0.2010	0.07727	2.60	0.0047
UN(3,1)	PersonID*burst	-0.04592	0.01443	-3.18	0.0015
UN(3,2)	PersonID*burst	0.008945	0.01379	0.65	0.5165
UN(3,3)	PersonID*burst	0.01198	0.004799	2.50	0.0063
Residual		0.5363	0.02047	26.19	<.0001

Fit Statistics
-2 Log Likelihood	7354.5
AIC (Smaller is Better)	7388.5
AICC (Smaller is Better)	7388.7
BIC (Smaller is Better)	7434.2

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
9	2351.18	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
7354.5	17	7388.5	7388.7	7407.0	7434.2	7451.2

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	1.3596	0.1210	166	11.23	<.0001	0.05	1.1206	1.5985
burst1	0.5191	0.09440	354	5.50	<.0001	0.05	0.3334	0.7047
burst1*burst1	-0.1037	0.02312	331	-4.49	<.0001	0.05	-0.1491	-0.05821
slope12	-0.2269	0.04802	460	-4.72	<.0001	0.05	-0.3212	-0.1325
slope26	-0.00483	0.02231	492	-0.22	0.8287	0.05	-0.04866	0.03900
burst1*slope26	-0.07785	0.02700	461	-2.88	0.0041	0.05	-0.1309	-0.02478
burst1burst1slope26	0.01949	0.006656	459	2.93	0.0036	0.05	0.006413	0.03257

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	354	30.24	30.24	<.0001	<.0001
burst1*burst1	1	331	20.12	20.12	<.0001	<.0001
slope12	1	460	22.32	22.32	<.0001	<.0001
slope26	1	492	0.05	0.05	0.8286	0.8287
burst1*slope26	1	461	8.31	8.31	0.0039	0.0041
burst1burst1slope26	1	459	8.58	8.58	0.0034	0.0036

Estimates
Label	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Slope26 at Burst 1	-0.00483	0.02231	492	-0.22	0.8287	0.05	-0.04866	0.03900
Slope26 at Burst 2	-0.06318	0.01556	492	-4.06	<.0001	0.05	-0.09375	-0.03262
Slope26 at Burst 3	-0.08255	0.01783	492	-4.63	<.0001	0.05	-0.1176	-0.04752
Slope26 at Burst 4	-0.06293	0.01605	492	-3.92	0.0001	0.05	-0.09447	-0.03139
Slope26 at Burst 5	-0.00433	0.02563	479	-0.17	0.8660	0.05	-0.05469	0.04604

Likelihood Ratio Test for FitRandSlope12at2S vs. FitRandSlope26at2S

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitRandSlope12at2S	7379.4	14	7407.4	7445.0	.	.	.
FitRandSlope26at2S	7354.5	17	7388.5	7434.2	24.9667	3	.00001569

Total R2 (% Reduction) for PredEmpty3S vs. PredUncS

Name	PredCorr	TotalR2	TotalR2Diff
PredEmpty3S	.	.	.
PredUncS	0.15826	0.025048	.

Predicted Outcomes for Fake People

burst1	slope12	slope26	Pred
0	-1	0	1.58646
0	0	0	1.35959
0	0	1	1.35476
0	0	2	1.34993
0	0	3	1.34510
0	0	4	1.34027
1	-1	0	2.00187
1	0	0	1.77500
1	0	1	1.71182
1	0	2	1.64863
1	0	3	1.58545
1	0	4	1.52227
2	-1	0	2.20993
2	0	0	1.98306
2	0	1	1.90051
2	0	2	1.81796
2	0	3	1.73541
2	0	4	1.65286
3	-1	0	2.21064
3	0	0	1.98377
3	0	1	1.92084
3	0	2	1.85790
3	0	3	1.79497
3	0	4	1.73204
4	-1	0	2.00400
4	0	0	1.77712
4	0	1	1.77279
4	0	2	1.76847
4	0	3	1.76414
4	0	4	1.75981

Ch 10b: Piecewise Session Slopes (Slope26 by Quadratic Burst Only)

Add Random Linear Slope26 Across Persons for Symptoms

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	symptoms
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	13
Columns in X	7
Columns in Z per Subject	18
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2752
Number of Observations Not Used	0

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	9705.66306286
1	2	7353.70456664	0.00087313
2	1	7352.62337312	0.00001502
3	1	7352.60592460	0.00000001

Convergence criteria met.

Estimated G Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13	Col14	Col15	Col16	Col17	Col18
1	Intercept	101		0.9829	0.03816	-0.01346
2	burst1	101		0.03816	0.01224	0.002769
3	slope26	101		-0.01346	0.002769	0.001608
4	Intercept	101	1				0.5058	0.1053	-0.04249
5	slope12	101	1				0.1053	0.2011	0.007473
6	slope26	101	1				-0.04249	0.007473	0.01062
7	Intercept	101	2							0.5058	0.1053	-0.04249
8	slope12	101	2							0.1053	0.2011	0.007473
9	slope26	101	2							-0.04249	0.007473	0.01062
10	Intercept	101	3										0.5058	0.1053	-0.04249
11	slope12	101	3										0.1053	0.2011	0.007473
12	slope26	101	3										-0.04249	0.007473	0.01062
13	Intercept	101	4													0.5058	0.1053	-0.04249
14	slope12	101	4													0.1053	0.2011	0.007473
15	slope26	101	4													-0.04249	0.007473	0.01062
16	Intercept	101	5																0.5058	0.1053	-0.04249
17	slope12	101	5																0.1053	0.2011	0.007473
18	slope26	101	5																-0.04249	0.007473	0.01062

Estimated G Correlation Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13	Col14	Col15	Col16	Col17	Col18
1	Intercept	101		1.0000	0.3480	-0.3386
2	burst1	101		0.3480	1.0000	0.6243
3	slope26	101		-0.3386	0.6243	1.0000
4	Intercept	101	1				1.0000	0.3303	-0.5799
5	slope12	101	1				0.3303	1.0000	0.1618
6	slope26	101	1				-0.5799	0.1618	1.0000
7	Intercept	101	2							1.0000	0.3303	-0.5799
8	slope12	101	2							0.3303	1.0000	0.1618
9	slope26	101	2							-0.5799	0.1618	1.0000
10	Intercept	101	3										1.0000	0.3303	-0.5799
11	slope12	101	3										0.3303	1.0000	0.1618
12	slope26	101	3										-0.5799	0.1618	1.0000
13	Intercept	101	4													1.0000	0.3303	-0.5799
14	slope12	101	4													0.3303	1.0000	0.1618
15	slope26	101	4													-0.5799	0.1618	1.0000
16	Intercept	101	5																1.0000	0.3303	-0.5799
17	slope12	101	5																0.3303	1.0000	0.1618
18	slope26	101	5																-0.5799	0.1618	1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr Z
UN(1,1)	PersonID	0.9829	0.1851	5.31	<.0001
UN(2,1)	PersonID	0.03816	0.03270	1.17	0.2432
UN(2,2)	PersonID	0.01224	0.01003	1.22	0.1113
UN(3,1)	PersonID	-0.01346	0.01474	-0.91	0.3612
UN(3,2)	PersonID	0.002769	0.002982	0.93	0.3532
UN(3,3)	PersonID	0.001608	0.002111	0.76	0.2231
UN(1,1)	PersonID*burst	0.5058	0.06564	7.71	<.0001
UN(2,1)	PersonID*burst	0.1053	0.05320	1.98	0.0477
UN(2,2)	PersonID*burst	0.2011	0.07729	2.60	0.0046
UN(3,1)	PersonID*burst	-0.04249	0.01464	-2.90	0.0037
UN(3,2)	PersonID*burst	0.007473	0.01387	0.54	0.5900
UN(3,3)	PersonID*burst	0.01062	0.005053	2.10	0.0178
Residual		0.5363	0.02048	26.19	<.0001

Fit Statistics
-2 Log Likelihood	7352.6
AIC (Smaller is Better)	7392.6
AICC (Smaller is Better)	7392.9
BIC (Smaller is Better)	7446.2

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
12	2353.06	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
7352.6	20	7392.6	7392.9	7414.4	7446.2	7466.2

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	1.3597	0.1224	153	11.11	<.0001	0.05	1.1179	1.6015
burst1	0.5183	0.09361	349	5.54	<.0001	0.05	0.3342	0.7024
burst1*burst1	-0.1034	0.02291	327	-4.51	<.0001	0.05	-0.1484	-0.05830
slope12	-0.2270	0.04803	460	-4.73	<.0001	0.05	-0.3214	-0.1327
slope26	-0.00493	0.02235	485	-0.22	0.8255	0.05	-0.04885	0.03899
burst1*slope26	-0.07791	0.02664	372	-2.92	0.0037	0.05	-0.1303	-0.02553
burst1burst1slope26	0.01951	0.006566	371	2.97	0.0032	0.05	0.006597	0.03242

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	349	30.65	30.65	<.0001	<.0001
burst1*burst1	1	327	20.36	20.36	<.0001	<.0001
slope12	1	460	22.35	22.35	<.0001	<.0001
slope26	1	485	0.05	0.05	0.8254	0.8255
burst1*slope26	1	372	8.55	8.55	0.0034	0.0037
burst1burst1slope26	1	371	8.83	8.83	0.0030	0.0032

Likelihood Ratio Test for FitRandSlope26at2S vs. FitRandSlope26at23S

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitRandSlope26at2S	7354.5	17	7388.5	7434.2	.	.	.
FitRandSlope26at23S	7352.6	20	7392.6	7446.2	1.87447	3	0.59887

Ch 10b: Final Unconditional Model for Symptoms

Remove Level-2 Random Effects Variances and Covariances

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	symptoms
Covariance Structure	Unstructured
Subject Effect	PersonID
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	4
Columns in X	7
Columns in Z per Subject	2
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2752
Number of Observations Not Used	0

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	9705.66306286
1	2	7769.36120239	0.00057541
2	1	7768.48285951	0.00002872
3	1	7768.44255751	0.00000009
4	1	7768.44243753	0.00000000

Convergence criteria met.

Estimated G Matrix
Row	Effect	PersonID: Person ID Variable	Col1	Col2
1	Intercept	101	1.1603	-0.02102
2	burst1	101	-0.02102	0.05516

Estimated G Correlation Matrix
Row	Effect	PersonID: Person ID Variable	Col1	Col2
1	Intercept	101	1.0000	-0.08310
2	burst1	101	-0.08310	1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr Z
UN(1,1)	PersonID	1.1603	0.1721	6.74	<.0001
UN(2,1)	PersonID	-0.02102	0.03267	-0.64	0.5199
UN(2,2)	PersonID	0.05516	0.01122	4.92	<.0001
Residual		0.8129	0.02286	35.56	<.0001

Fit Statistics
-2 Log Likelihood	7768.4
AIC (Smaller is Better)	7790.4
AICC (Smaller is Better)	7790.5
BIC (Smaller is Better)	7819.9

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
3	1937.22	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
7768.4	11	7790.4	7790.5	7802.4	7819.9	7830.9

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	1.3626	0.1171	148	11.64	<.0001	0.05	1.1312	1.5940
burst1	0.5221	0.06776	1769	7.70	<.0001	0.05	0.3892	0.6549
burst1*burst1	-0.1029	0.01579	2606	-6.52	<.0001	0.05	-0.1338	-0.07192
slope12	-0.2293	0.05320	2530	-4.31	<.0001	0.05	-0.3336	-0.1250
slope26	-0.00531	0.02369	2531	-0.22	0.8227	0.05	-0.05177	0.04115
burst1*slope26	-0.07892	0.02808	2530	-2.81	0.0050	0.05	-0.1340	-0.02386
burst1burst1slope26	0.01994	0.006918	2530	2.88	0.0040	0.05	0.006371	0.03350

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	1769	59.36	59.36	<.0001	<.0001
burst1*burst1	1	2606	42.47	42.47	<.0001	<.0001
slope12	1	2530	18.58	18.58	<.0001	<.0001
slope26	1	2531	0.05	0.05	0.8227	0.8227
burst1*slope26	1	2530	7.90	7.90	0.0049	0.0050
burst1burst1slope26	1	2530	8.31	8.31	0.0040	0.0040

Likelihood Ratio Test for FitNo2S vs. FitRandSlope26at2S

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitNo2S	7768.4	11	7790.4	7819.9	.	.	.
FitRandSlope26at2S	7354.5	17	7388.5	7434.2	413.962	6	0

Eq 10b.6: Saturated Means for Burst by Session

Three-Level Model for the Variance for Positive Affect

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	posaff
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	3
Columns in X	42
Columns in Z per Subject	6
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2747
Number of Observations Not Used	5

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	6038.05309793
1	2	3485.48304348	0.00000027
2	1	3485.48283157	0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr > Z
UN(1,1)	PersonID	0.3258	0.04779	6.82	<.0001
UN(1,1)	PersonID*burst	0.05677	0.006275	9.05	<.0001
Residual		0.1533	0.004535	33.80	<.0001

Fit Statistics
-2 Log Likelihood	3485.5
AIC (Smaller is Better)	3551.5
AICC (Smaller is Better)	3552.3
BIC (Smaller is Better)	3640.0

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
2	2552.57	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
3485.5	33	3551.5	3552.3	3587.4	3640.0	3673.0

Solution for Fixed Effects
Effect	burst: Measurement Burst (1-5)	session: Within-Burst Session (1-6)	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept			2.4391	0.07676	339	31.77	<.0001	0.05	2.2881	2.5901
session		1	-0.04546	0.06333	2286	-0.72	0.4730	0.05	-0.1697	0.07873
session		2	-0.04026	0.06333	2286	-0.64	0.5250	0.05	-0.1645	0.08393
session		3	-0.01948	0.06333	2286	-0.31	0.7584	0.05	-0.1437	0.1047
session		4	0.01168	0.06333	2286	0.18	0.8536	0.05	-0.1125	0.1359
session		5	0.06103	0.06333	2286	0.96	0.3353	0.05	-0.06316	0.1852
session		6	0	.	.	.	.	.	.	.
burst	1		0.2326	0.06985	1647	3.33	0.0009	0.05	0.09559	0.3696
burst	2		0.2018	0.07101	1647	2.84	0.0045	0.05	0.06250	0.3410
burst	3		0.1112	0.07124	1649	1.56	0.1189	0.05	-0.02857	0.2509
burst	4		0.02583	0.07232	1648	0.36	0.7210	0.05	-0.1160	0.1677
burst	5		0	.	.	.	.	.	.	.
burst*session	1	1	0.1755	0.08343	2289	2.10	0.0355	0.05	0.01188	0.3391
burst*session	1	2	0.005638	0.08314	2287	0.07	0.9459	0.05	-0.1574	0.1687
burst*session	1	3	-0.1388	0.08334	2289	-1.67	0.0960	0.05	-0.3022	0.02464
burst*session	1	4	-0.06807	0.08340	2288	-0.82	0.4145	0.05	-0.2316	0.09548
burst*session	1	5	-0.1707	0.08324	2288	-2.05	0.0404	0.05	-0.3339	-0.00744
burst*session	1	6	0	.	.	.	.	.	.	.
burst*session	2	1	0.1232	0.08500	2287	1.45	0.1474	0.05	-0.04350	0.2899
burst*session	2	2	-0.02785	0.08500	2287	-0.33	0.7432	0.05	-0.1945	0.1388
burst*session	2	3	-0.04999	0.08507	2285	-0.59	0.5569	0.05	-0.2168	0.1168
burst*session	2	4	-0.04537	0.08507	2285	-0.53	0.5939	0.05	-0.2122	0.1215
burst*session	2	5	-0.1452	0.08507	2285	-1.71	0.0879	0.05	-0.3121	0.02159
burst*session	2	6	0	.	.	.	.	.	.	.
burst*session	3	1	-0.03374	0.08542	2289	-0.39	0.6929	0.05	-0.2012	0.1338
burst*session	3	2	-0.07371	0.08548	2285	-0.86	0.3886	0.05	-0.2413	0.09391
burst*session	3	3	-0.08589	0.08548	2285	-1.00	0.3151	0.05	-0.2535	0.08174
burst*session	3	4	-0.05685	0.08548	2285	-0.67	0.5061	0.05	-0.2245	0.1108
burst*session	3	5	-0.06592	0.08560	2286	-0.77	0.4414	0.05	-0.2338	0.1019
burst*session	3	6	0	.	.	.	.	.	.	.
burst*session	4	1	0.05465	0.08680	2285	0.63	0.5290	0.05	-0.1156	0.2249
burst*session	4	2	-0.01031	0.08680	2285	-0.12	0.9055	0.05	-0.1805	0.1599
burst*session	4	3	-0.00270	0.08694	2286	-0.03	0.9752	0.05	-0.1732	0.1678
burst*session	4	4	0.03429	0.08680	2285	0.40	0.6928	0.05	-0.1359	0.2045
burst*session	4	5	-0.03575	0.08680	2285	-0.41	0.6805	0.05	-0.2060	0.1345
burst*session	4	6	0	.	.	.	.	.	.	.
burst*session	5	1	0	.	.	.	.	.	.	.
burst*session	5	2	0	.	.	.	.	.	.	.
burst*session	5	3	0	.	.	.	.	.	.	.
burst*session	5	4	0	.	.	.	.	.	.	.
burst*session	5	5	0	.	.	.	.	.	.	.
burst*session	5	6	0	.	.	.	.	.	.	.

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
session	5	2287	19.00	3.80	0.0019	0.0020
burst	4	354	33.82	8.45	<.0001	<.0001
burst*session	20	2287	38.12	1.91	0.0086	0.0090

Least Squares Means
Effect	burst: Measurement Burst (1-5)	session: Within-Burst Session (1-6)	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
session		1	2.5718	0.05932	126	43.36	<.0001	0.05	2.4544	2.6892
session		2	2.4918	0.05931	126	42.01	<.0001	0.05	2.3745	2.6092
session		3	2.4784	0.05934	126	41.77	<.0001	0.05	2.3610	2.5958
session		4	2.5378	0.05935	126	42.76	<.0001	0.05	2.4204	2.6553
session		5	2.5309	0.05933	126	42.66	<.0001	0.05	2.4135	2.6483
session		6	2.5533	0.05936	126	43.01	<.0001	0.05	2.4359	2.6708
burst	1		2.6335	0.06153	145	42.80	<.0001	0.05	2.5119	2.7551
burst	2		2.6112	0.06272	155	41.63	<.0001	0.05	2.4873	2.7351
burst	3		2.4921	0.06299	158	39.57	<.0001	0.05	2.3677	2.6166
burst	4		2.4662	0.06364	164	38.75	<.0001	0.05	2.3405	2.5919
burst	5		2.4337	0.06484	175	37.53	<.0001	0.05	2.3057	2.5616
burst*session	1	1	2.8017	0.07078	253	39.59	<.0001	0.05	2.6623	2.9411
burst*session	1	2	2.6370	0.07044	248	37.44	<.0001	0.05	2.4983	2.7758
burst*session	1	3	2.5134	0.07066	251	35.57	<.0001	0.05	2.3742	2.6526
burst*session	1	4	2.6153	0.07078	253	36.95	<.0001	0.05	2.4759	2.7547
burst*session	1	5	2.5620	0.07055	250	36.31	<.0001	0.05	2.4231	2.7010
burst*session	1	6	2.6717	0.07089	255	37.69	<.0001	0.05	2.5321	2.8113
burst*session	2	1	2.7186	0.07253	276	37.48	<.0001	0.05	2.5758	2.8614
burst*session	2	2	2.5727	0.07253	276	35.47	<.0001	0.05	2.4299	2.7155
burst*session	2	3	2.5714	0.07268	278	35.38	<.0001	0.05	2.4283	2.7144
burst*session	2	4	2.6072	0.07268	278	35.87	<.0001	0.05	2.4641	2.7502
burst*session	2	5	2.5566	0.07268	278	35.18	<.0001	0.05	2.4136	2.6997
burst*session	2	6	2.6408	0.07268	278	36.34	<.0001	0.05	2.4978	2.7839
burst*session	3	1	2.4711	0.07293	281	33.88	<.0001	0.05	2.3275	2.6146
burst*session	3	2	2.4363	0.07309	284	33.33	<.0001	0.05	2.2924	2.5801
burst*session	3	3	2.4449	0.07309	284	33.45	<.0001	0.05	2.3010	2.5887
burst*session	3	4	2.5051	0.07309	284	34.27	<.0001	0.05	2.3612	2.6490
burst*session	3	5	2.5454	0.07323	286	34.76	<.0001	0.05	2.4012	2.6895
burst*session	3	6	2.5502	0.07309	284	34.89	<.0001	0.05	2.4064	2.6941
burst*session	4	1	2.4741	0.07428	301	33.31	<.0001	0.05	2.3279	2.6203
burst*session	4	2	2.4143	0.07428	301	32.50	<.0001	0.05	2.2682	2.5605
burst*session	4	3	2.4427	0.07444	303	32.81	<.0001	0.05	2.2962	2.5892
burst*session	4	4	2.5109	0.07428	301	33.80	<.0001	0.05	2.3647	2.6571
burst*session	4	5	2.4902	0.07428	301	33.52	<.0001	0.05	2.3440	2.6364
burst*session	4	6	2.4649	0.07428	301	33.18	<.0001	0.05	2.3187	2.6111
burst*session	5	1	2.3936	0.07657	336	31.26	<.0001	0.05	2.2430	2.5442
burst*session	5	2	2.3988	0.07657	336	31.33	<.0001	0.05	2.2482	2.5494
burst*session	5	3	2.4196	0.07657	336	31.60	<.0001	0.05	2.2690	2.5702
burst*session	5	4	2.4508	0.07657	336	32.01	<.0001	0.05	2.3002	2.6014
burst*session	5	5	2.5001	0.07657	336	32.65	<.0001	0.05	2.3495	2.6507
burst*session	5	6	2.4391	0.07676	339	31.77	<.0001	0.05	2.2881	2.5901

Eq 10b.7: Piecewise Session Slopes by Observed Burst

Three-Level Model for the Variance for Positive Affect

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	posaff
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	3
Columns in X	18
Columns in Z per Subject	6
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2747
Number of Observations Not Used	5

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	6042.30487667
1	2	3501.43655728	0.00000028
2	1	3501.43634315	0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr > Z
UN(1,1)	PersonID	0.3259	0.04781	6.82	<.0001
UN(1,1)	PersonID*burst	0.05654	0.006272	9.02	<.0001
Residual		0.1544	0.004567	33.80	<.0001

Fit Statistics
-2 Log Likelihood	3501.4
AIC (Smaller is Better)	3537.4
AICC (Smaller is Better)	3537.7
BIC (Smaller is Better)	3585.7

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
2	2540.87	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
3501.4	18	3537.4	3537.7	3557.0	3585.7	3603.7

Solution for Fixed Effects
Effect	burst: Measurement Burst (1-5)	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept		2.4091	0.07123	254	33.82	<.0001	0.05	2.2689	2.5494
slope12		0.01574	0.05664	2285	0.28	0.7812	0.05	-0.09534	0.1268
slope26		0.01621	0.01420	2286	1.14	0.2538	0.05	-0.01164	0.04406
burst	1	0.1682	0.05871	1020	2.86	0.0043	0.05	0.05296	0.2834
burst	2	0.1562	0.05976	1025	2.61	0.0091	0.05	0.03891	0.2734
burst	3	0.02133	0.06001	1029	0.36	0.7223	0.05	-0.09643	0.1391
burst	4	0.02557	0.06094	1029	0.42	0.6749	0.05	-0.09401	0.1452
burst	5	0	.	.	.	.	.	.	.
slope12*burst	1	-0.2403	0.07449	2286	-3.23	0.0013	0.05	-0.3864	-0.09425
slope12*burst	2	-0.1688	0.07606	2285	-2.22	0.0266	0.05	-0.3180	-0.01964
slope12*burst	3	-0.05611	0.07651	2289	-0.73	0.4634	0.05	-0.2061	0.09392
slope12*burst	4	-0.05492	0.07779	2285	-0.71	0.4803	0.05	-0.2075	0.09762
slope12*burst	5	0	.	.	.	.	.	.	.
slope26*burst	1	-0.00496	0.01864	2287	-0.27	0.7902	0.05	-0.04152	0.03160
slope26*burst	2	-0.00408	0.01907	2287	-0.21	0.8307	0.05	-0.04147	0.03332
slope26*burst	3	0.01662	0.01918	2285	0.87	0.3864	0.05	-0.02099	0.05423
slope26*burst	4	-0.00136	0.01948	2285	-0.07	0.9444	0.05	-0.03955	0.03684
slope26*burst	5	0	.	.	.	.	.	.	.

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
slope12	1	2287	14.32	14.32	0.0002	0.0002
slope26	1	2286	8.93	8.93	0.0028	0.0028
burst	4	1032	15.93	3.98	0.0031	0.0033
slope12*burst	4	2287	14.53	3.63	0.0058	0.0059
slope26*burst	4	2286	1.91	0.48	0.7531	0.7531

Estimates
Label	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Session 2 at Burst 1	2.5773	0.06639	197	38.82	<.0001	0.05	2.4464	2.7082
Session 2 at Burst 2	2.5653	0.06806	215	37.69	<.0001	0.05	2.4312	2.6995
Session 2 at Burst 3	2.4305	0.06847	220	35.50	<.0001	0.05	2.2955	2.5654
Session 2 at Burst 4	2.4347	0.06944	231	35.06	<.0001	0.05	2.2979	2.5715
Session 2 at Burst 5	2.4091	0.07123	254	33.82	<.0001	0.05	2.2689	2.5494
Slope12 at Burst 1	-0.2246	0.04838	2289	-4.64	<.0001	0.05	-0.3195	-0.1297
Slope12 at Burst 2	-0.1531	0.05077	2285	-3.02	0.0026	0.05	-0.2526	-0.05352
Slope12 at Burst 3	-0.04037	0.05143	2294	-0.79	0.4325	0.05	-0.1412	0.06047
Slope12 at Burst 4	-0.03918	0.05331	2285	-0.73	0.4625	0.05	-0.1437	0.06537
Slope12 at Burst 5	0.01574	0.05664	2285	0.28	0.7812	0.05	-0.09534	0.1268
Slope26 at Burst 1	0.01125	0.01208	2288	0.93	0.3518	0.05	-0.01244	0.03493
Slope26 at Burst 2	0.01213	0.01273	2288	0.95	0.3405	0.05	-0.01282	0.03709
Slope26 at Burst 3	0.03282	0.01289	2285	2.55	0.0110	0.05	0.007546	0.05810
Slope26 at Burst 4	0.01485	0.01333	2285	1.11	0.2653	0.05	-0.01128	0.04099
Slope26 at Burst 5	0.01621	0.01420	2286	1.14	0.2538	0.05	-0.01164	0.04406

Likelihood Ratio Test for FitPiecebyBurstMeansP vs. FitSatAllP

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitPiecebyBurstMeansP	3501.4	18	3537.4	3585.7	.	.	.
FitSatAllP	3485.5	33	3551.5	3640.0	15.9535	15	0.38515

Eq 10b.11and12: Piecewise Session Slopes, Linear Burst, Slope12 by Burst1or2

Three-Level Model for the Variance for Positive Affect

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	posaff
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	3
Columns in X	5
Columns in Z per Subject	6
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2747
Number of Observations Not Used	5

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	6047.08482900
1	2	3506.65017380	0.00000028
2	1	3506.64996030	0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr > Z
UN(1,1)	PersonID	0.3262	0.04783	6.82	<.0001
UN(1,1)	PersonID*burst	0.05668	0.006286	9.02	<.0001
Residual		0.1546	0.004576	33.80	<.0001

Fit Statistics
-2 Log Likelihood	3506.6
AIC (Smaller is Better)	3522.6
AICC (Smaller is Better)	3522.7
BIC (Smaller is Better)	3544.1

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
2	2540.43	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
3506.6	8	3522.6	3522.7	3531.4	3544.1	3552.1

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	2.5734	0.06065	138	42.43	<.0001	0.05	2.4535	2.6934
burst1	-0.04513	0.01007	389	-4.48	<.0001	0.05	-0.06492	-0.02533
slope12	-0.01197	0.02917	2314	-0.41	0.6815	0.05	-0.06918	0.04523
slope12*b1or2	-0.1926	0.04026	2356	-4.79	<.0001	0.05	-0.2716	-0.1137
slope26	0.01733	0.005814	2286	2.98	0.0029	0.05	0.005924	0.02873

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	389	20.09	20.09	<.0001	<.0001
slope12	1	2314	0.17	0.17	0.6814	0.6815
slope12*b1or2	1	2356	22.90	22.90	<.0001	<.0001
slope26	1	2286	8.88	8.88	0.0029	0.0029

Estimates
Label	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Slope12 at Burst 1 or 2	-0.2046	0.03242	2321	-6.31	<.0001	0.05	-0.2682	-0.1411

Likelihood Ratio Test for FitPieceBurst1or2P vs. FitPiecebyBurstMeansP

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitPieceBurst1or2P	3506.6	8	3522.6	3544.1	.	.	.
FitPiecebyBurstMeansP	3501.4	18	3537.4	3585.7	5.21362	10	0.87646

Likelihood Ratio Test for FitPieceBurst1or2P vs. FitSatAllP

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitPieceBurst1or2P	3506.6	8	3522.6	3544.1	.	.	.
FitSatAllP	3485.5	33	3551.5	3640.0	21.1671	25	0.68325

Ch 10b: Piecewise Session Slopes, Linear Burst, Slope12 by Burst1or2

Add Random Linear Burst across Persons for Positive Affect

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	posaff
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	5
Columns in X	5
Columns in Z per Subject	7
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2747
Number of Observations Not Used	5

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	6047.08482900
1	2	3483.11537113	0.00000896
2	1	3483.10827762	0.00000000

Convergence criteria met.

Estimated G Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7
1	Intercept	101		0.3170	-0.00303
2	burst1	101		-0.00303	0.007500
3	Intercept	101	1			0.03848
4	Intercept	101	2				0.03848
5	Intercept	101	3					0.03848
6	Intercept	101	4						0.03848
7	Intercept	101	5							0.03848

Estimated G Correlation Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7
1	Intercept	101		1.0000	-0.06224
2	burst1	101		-0.06224	1.0000
3	Intercept	101	1			1.0000
4	Intercept	101	2				1.0000
5	Intercept	101	3					1.0000
6	Intercept	101	4						1.0000
7	Intercept	101	5							1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr Z
UN(1,1)	PersonID	0.3170	0.04924	6.44	<.0001
UN(2,1)	PersonID	-0.00303	0.007902	-0.38	0.7009
UN(2,2)	PersonID	0.007500	0.002198	3.41	0.0003
UN(1,1)	PersonID*burst	0.03848	0.005679	6.78	<.0001
Residual		0.1547	0.004576	33.80	<.0001

Fit Statistics
-2 Log Likelihood	3483.1
AIC (Smaller is Better)	3503.1
AICC (Smaller is Better)	3503.2
BIC (Smaller is Better)	3529.9

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
4	2563.98	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
3483.1	10	3503.1	3503.2	3514.0	3529.9	3539.9

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	2.5741	0.05906	118	43.58	<.0001	0.05	2.4571	2.6910
burst1	-0.04665	0.01271	104	-3.67	0.0004	0.05	-0.07185	-0.02145
slope12	-0.01140	0.02915	2319	-0.39	0.6957	0.05	-0.06856	0.04576
slope12*b1or2	-0.1940	0.04018	2370	-4.83	<.0001	0.05	-0.2728	-0.1153
slope26	0.01735	0.005815	2286	2.98	0.0029	0.05	0.005948	0.02875

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	104	13.48	13.48	0.0002	0.0004
slope12	1	2319	0.15	0.15	0.6957	0.6957
slope12*b1or2	1	2370	23.33	23.33	<.0001	<.0001
slope26	1	2286	8.90	8.90	0.0028	0.0029

Likelihood Ratio Test for FitPieceBurst1or2P vs. FitRandBurstLin3P

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitPieceBurst1or2P	3506.6	8	3522.6	3544.1	.	.	.
FitRandBurstLin3P	3483.1	10	3503.1	3529.9	23.5417	2	.000007727

Ch 10b: Piecewise Session Slopes, Linear Burst, Slope12 by Burst1or2

Add Fixed and Random Quadratic Burst across Persons for Positive Affect

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	posaff
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	8
Columns in X	6
Columns in Z per Subject	8
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2747
Number of Observations Not Used	5

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	6046.91001639
1	3	3477.90697093	0.00074754
2	1	3477.26514270	0.00001938
3	1	3477.24961262	0.00000002
4	1	3477.24959764	0.00000000

Convergence criteria met.

Estimated G Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8
1	Intercept	101		0.3107	0.001891	-0.00233
2	burst1	101		0.001891	0.03777	-0.00637
3	burst1*burst1	101		-0.00233	-0.00637	0.001321
4	Intercept	101	1				0.03209
5	Intercept	101	2					0.03209
6	Intercept	101	3						0.03209
7	Intercept	101	4							0.03209
8	Intercept	101	5								0.03209

Estimated G Correlation Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8
1	Intercept	101		1.0000	0.01746	-0.1152
2	burst1	101		0.01746	1.0000	-0.9024
3	burst1*burst1	101		-0.1152	-0.9024	1.0000
4	Intercept	101	1				1.0000
5	Intercept	101	2					1.0000
6	Intercept	101	3						1.0000
7	Intercept	101	4							1.0000
8	Intercept	101	5								1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr Z
UN(1,1)	PersonID	0.3107	0.04990	6.23	<.0001
UN(2,1)	PersonID	0.001891	0.02227	0.08	0.9323
UN(2,2)	PersonID	0.03777	0.01775	2.13	0.0167
UN(3,1)	PersonID	-0.00233	0.005029	-0.46	0.6425
UN(3,2)	PersonID	-0.00637	0.003927	-1.62	0.1045
UN(3,3)	PersonID	0.001321	0.000930	1.42	0.0777
UN(1,1)	PersonID*burst	0.03209	0.006205	5.17	<.0001
Residual		0.1547	0.004576	33.80	<.0001

Fit Statistics
-2 Log Likelihood	3477.2
AIC (Smaller is Better)	3505.2
AICC (Smaller is Better)	3505.4
BIC (Smaller is Better)	3542.8

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
7	2569.66	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
3477.2	14	3505.2	3505.4	3520.5	3542.8	3556.8

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	2.5781	0.05944	118	43.38	<.0001	0.05	2.4604	2.6958
burst1	-0.05927	0.03434	107	-1.73	0.0873	0.05	-0.1274	0.008812
slope12	-0.01155	0.02916	2316	-0.40	0.6921	0.05	-0.06874	0.04564
slope12*b1or2	-0.1939	0.04022	2360	-4.82	<.0001	0.05	-0.2728	-0.1151
slope26	0.01735	0.005815	2286	2.98	0.0029	0.05	0.005949	0.02875
burst1*burst1	0.003495	0.007876	103	0.44	0.6582	0.05	-0.01213	0.01911

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	107	2.98	2.98	0.0844	0.0873
slope12	1	2316	0.16	0.16	0.6921	0.6921
slope12*b1or2	1	2360	23.26	23.26	<.0001	<.0001
slope26	1	2286	8.91	8.91	0.0028	0.0029
burst1*burst1	1	103	0.20	0.20	0.6572	0.6582

Likelihood Ratio Test for FitRandBurstLin3P vs. FitRandBurstQuad3P

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitRandBurstLin3P	3483.1	10	3503.1	3529.9	.	.	.
FitRandBurstQuad3P	3477.2	14	3505.2	3542.8	5.85868	4	0.20995

Ch 10b: Piecewise Session Slopes, Linear Burst, Slope12 by Burst1or2

Add Random Linear Slope12 across Bursts for Positive Affect

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	posaff
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	7
Columns in X	5
Columns in Z per Subject	12
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2747
Number of Observations Not Used	5

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	6047.08482900
1	3	3482.73965782	0.01694400
2	1	3466.70760706	0.00294603
3	1	3464.10002716	0.00012873
4	1	3463.99488305	0.00000030
5	1	3463.99464453	0.00000000

Convergence criteria met.

Estimated G Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12
1	Intercept	101		0.3176	-0.00303
2	burst1	101		-0.00303	0.007495
3	Intercept	101	1			0.04180	0.01004
4	slope12	101	1			0.01004	0.06364
5	Intercept	101	2					0.04180	0.01004
6	slope12	101	2					0.01004	0.06364
7	Intercept	101	3							0.04180	0.01004
8	slope12	101	3							0.01004	0.06364
9	Intercept	101	4									0.04180	0.01004
10	slope12	101	4									0.01004	0.06364
11	Intercept	101	5											0.04180	0.01004
12	slope12	101	5											0.01004	0.06364

Estimated G Correlation Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12
1	Intercept	101		1.0000	-0.06215
2	burst1	101		-0.06215	1.0000
3	Intercept	101	1			1.0000	0.1946
4	slope12	101	1			0.1946	1.0000
5	Intercept	101	2					1.0000	0.1946
6	slope12	101	2					0.1946	1.0000
7	Intercept	101	3							1.0000	0.1946
8	slope12	101	3							0.1946	1.0000
9	Intercept	101	4									1.0000	0.1946
10	slope12	101	4									0.1946	1.0000
11	Intercept	101	5											1.0000	0.1946
12	slope12	101	5											0.1946	1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr Z
UN(1,1)	PersonID	0.3176	0.04950	6.42	<.0001
UN(2,1)	PersonID	-0.00303	0.007912	-0.38	0.7015
UN(2,2)	PersonID	0.007495	0.002197	3.41	0.0003
UN(1,1)	PersonID*burst	0.04180	0.006376	6.56	<.0001
UN(2,1)	PersonID*burst	0.01004	0.008263	1.21	0.2245
UN(2,2)	PersonID*burst	0.06364	0.01665	3.82	<.0001
Residual		0.1440	0.004766	30.22	<.0001

Fit Statistics
-2 Log Likelihood	3464.0
AIC (Smaller is Better)	3488.0
AICC (Smaller is Better)	3488.1
BIC (Smaller is Better)	3520.2

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
6	2583.09	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
3464.0	12	3488.0	3488.1	3501.0	3520.2	3532.2

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	2.5737	0.05908	117	43.57	<.0001	0.05	2.4567	2.6907
burst1	-0.04648	0.01274	104	-3.65	0.0004	0.05	-0.07175	-0.02121
slope12	-0.01053	0.03216	602	-0.33	0.7436	0.05	-0.07369	0.05264
slope12*b1or2	-0.1957	0.04524	471	-4.33	<.0001	0.05	-0.2846	-0.1068
slope26	0.01729	0.005612	1829	3.08	0.0021	0.05	0.006287	0.02830

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	104	13.30	13.30	0.0003	0.0004
slope12	1	602	0.11	0.11	0.7434	0.7436
slope12*b1or2	1	471	18.72	18.72	<.0001	<.0001
slope26	1	1829	9.50	9.50	0.0021	0.0021

Likelihood Ratio Test for FitRandBurstLin3P vs. FitRandSlope12at2P

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitRandBurstLin3P	3483.1	10	3503.1	3529.9	.	.	.
FitRandSlope12at2P	3464.0	12	3488.0	3520.2	19.1136	2	.000070718

Ch 10b: Piecewise Session Slopes, Linear Burst, Slope12 by Burst1or2

Add Random Linear Slope12 across Persons for Positive Affect

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	posaff
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	10
Columns in X	5
Columns in Z per Subject	13
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2747
Number of Observations Not Used	5

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	6047.08482900
1	3	3436.86239911	0.00003088
2	1	3436.83703273	0.00000003
3	1	3436.83700902	0.00000000

Convergence criteria met.

Estimated G Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13
1	Intercept	101		0.3370	-0.00325	0.05902
2	burst1	101		-0.00325	0.007515	0.001612
3	slope12	101		0.05902	0.001612	0.03559
4	Intercept	101	1				0.03955	0.000291
5	slope12	101	1				0.000291	0.02811
6	Intercept	101	2						0.03955	0.000291
7	slope12	101	2						0.000291	0.02811
8	Intercept	101	3								0.03955	0.000291
9	slope12	101	3								0.000291	0.02811
10	Intercept	101	4										0.03955	0.000291
11	slope12	101	4										0.000291	0.02811
12	Intercept	101	5												0.03955	0.000291
13	slope12	101	5												0.000291	0.02811

Estimated G Correlation Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13
1	Intercept	101		1.0000	-0.06449	0.5389
2	burst1	101		-0.06449	1.0000	0.09855
3	slope12	101		0.5389	0.09855	1.0000
4	Intercept	101	1				1.0000	0.008740
5	slope12	101	1				0.008740	1.0000
6	Intercept	101	2						1.0000	0.008740
7	slope12	101	2						0.008740	1.0000
8	Intercept	101	3								1.0000	0.008740
9	slope12	101	3								0.008740	1.0000
10	Intercept	101	4										1.0000	0.008740
11	slope12	101	4										0.008740	1.0000
12	Intercept	101	5												1.0000	0.008740
13	slope12	101	5												0.008740	1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr Z
UN(1,1)	PersonID	0.3370	0.05212	6.47	<.0001
UN(2,1)	PersonID	-0.00325	0.008103	-0.40	0.6888
UN(2,2)	PersonID	0.007515	0.002202	3.41	0.0003
UN(3,1)	PersonID	0.05902	0.01873	3.15	0.0016
UN(3,2)	PersonID	0.001612	0.003479	0.46	0.6432
UN(3,3)	PersonID	0.03559	0.01181	3.01	0.0013
UN(1,1)	PersonID*burst	0.03955	0.006042	6.55	<.0001
UN(2,1)	PersonID*burst	0.000291	0.007128	0.04	0.9674
UN(2,2)	PersonID*burst	0.02811	0.01618	1.74	0.0411
Residual		0.1440	0.004766	30.22	<.0001

Fit Statistics
-2 Log Likelihood	3436.8
AIC (Smaller is Better)	3466.8
AICC (Smaller is Better)	3467.0
BIC (Smaller is Better)	3507.1

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
9	2610.25	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
3436.8	15	3466.8	3467.0	3483.1	3507.1	3522.1

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	2.5725	0.06049	115	42.53	<.0001	0.05	2.4527	2.6923
burst1	-0.04586	0.01268	102	-3.62	0.0005	0.05	-0.07102	-0.02070
slope12	-0.01755	0.03557	236	-0.49	0.6223	0.05	-0.08762	0.05253
slope12*b1or2	-0.1953	0.04218	385	-4.63	<.0001	0.05	-0.2782	-0.1123
slope26	0.01726	0.005611	1829	3.08	0.0021	0.05	0.006252	0.02826

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	102	13.07	13.07	0.0003	0.0005
slope12	1	236	0.24	0.24	0.6218	0.6223
slope12*b1or2	1	385	21.42	21.42	<.0001	<.0001
slope26	1	1829	9.46	9.46	0.0021	0.0021

Likelihood Ratio Test for FitRandSlope12at2P vs. FitRandSlope12at23P

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitRandSlope12at2P	3464.0	12	3488.0	3520.2	.	.	.
FitRandSlope12at23P	3436.8	15	3466.8	3507.1	27.1576	3	.000005456

Ch 10b: Piecewise Session Slopes, Linear Burst, Slope12 by Burst1or2

Add Random Slope12*b1or2 across Persons for Positive Affect

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	posaff
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	14
Columns in X	5
Columns in Z per Subject	14
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2747
Number of Observations Not Used	5

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	6047.08482900
1	3	3460.11807196	45.05167639
2	2	3443.37997462	0.02980557
3	1	3439.85575902	0.00657076
4	2	3433.46810576	0.00129934
5	1	3432.27074092	0.00008514
6	1	3432.19874266	0.00000046
7	1	3432.19836736	0.00000000

Convergence criteria met.

Estimated G Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13	Col14
1	Intercept	101		0.3369	-0.00289	0.05655	0.000524
2	burst1	101		-0.00289	0.006685	-0.00124	0.008535
3	slope12	101		0.05655	-0.00124	0.04774	-0.01683
4	slope12*b1or2	101		0.000524	0.008535	-0.01683	0.009455
5	Intercept	101	1					0.04095	0.004997
6	slope12	101	1					0.004997	0.02678
7	Intercept	101	2							0.04095	0.004997
8	slope12	101	2							0.004997	0.02678
9	Intercept	101	3									0.04095	0.004997
10	slope12	101	3									0.004997	0.02678
11	Intercept	101	4											0.04095	0.004997
12	slope12	101	4											0.004997	0.02678
13	Intercept	101	5													0.04095	0.004997
14	slope12	101	5													0.004997	0.02678

Estimated G Correlation Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13	Col14
1	Intercept	101		1.0000	-0.06083	0.4459	0.009291
2	burst1	101		-0.06083	1.0000	-0.06922	1.0000
3	slope12	101		0.4459	-0.06922	1.0000	-0.7921
4	slope12*b1or2	101		0.009291	1.0000	-0.7921	1.0000
5	Intercept	101	1					1.0000	0.1509
6	slope12	101	1					0.1509	1.0000
7	Intercept	101	2							1.0000	0.1509
8	slope12	101	2							0.1509	1.0000
9	Intercept	101	3									1.0000	0.1509
10	slope12	101	3									0.1509	1.0000
11	Intercept	101	4											1.0000	0.1509
12	slope12	101	4											0.1509	1.0000
13	Intercept	101	5													1.0000	0.1509
14	slope12	101	5													0.1509	1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr Z
UN(1,1)	PersonID	0.3369	0.05239	6.43	<.0001
UN(2,1)	PersonID	-0.00289	0.008040	-0.36	0.7196
UN(2,2)	PersonID	0.006685	0.002187	3.06	0.0011
UN(3,1)	PersonID	0.05655	0.02298	2.46	0.0139
UN(3,2)	PersonID	-0.00124	0.004430	-0.28	0.7801
UN(3,3)	PersonID	0.04774	0.01839	2.60	0.0047
UN(4,1)	PersonID	0.000524	0.02754	0.02	0.9848
UN(4,2)	PersonID	0.008535	0.006066	1.41	0.1594
UN(4,3)	PersonID	-0.01683	0.01901	-0.89	0.3760
UN(4,4)	PersonID	0.009455	0.03103	0.30	0.3803
UN(1,1)	PersonID*burst	0.04095	0.006344	6.46	<.0001
UN(2,1)	PersonID*burst	0.004997	0.008249	0.61	0.5447
UN(2,2)	PersonID*burst	0.02678	0.01879	1.42	0.0771
Residual		0.1440	0.004765	30.22	<.0001

Fit Statistics
-2 Log Likelihood	3432.2
AIC (Smaller is Better)	3470.2
AICC (Smaller is Better)	3470.5
BIC (Smaller is Better)	3521.2

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
13	2614.89	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
3432.2	19	3470.2	3470.5	3490.9	3521.2	3540.2

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	2.5722	0.06053	115	42.49	<.0001	0.05	2.4523	2.6921
burst1	-0.04505	0.01236	96.5	-3.64	0.0004	0.05	-0.06959	-0.02051
slope12	-0.01641	0.03729	119	-0.44	0.6607	0.05	-0.09025	0.05743
slope12*b1or2	-0.1972	0.04316	97.3	-4.57	<.0001	0.05	-0.2829	-0.1116
slope26	0.01726	0.005611	1829	3.08	0.0021	0.05	0.006254	0.02827

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	96.5	13.28	13.28	0.0003	0.0004
slope12	1	119	0.19	0.19	0.6599	0.6607
slope12*b1or2	1	97.3	20.88	20.88	<.0001	<.0001
slope26	1	1829	9.46	9.46	0.0021	0.0021

Likelihood Ratio Test for FitRandSlope12at23P vs. FitRandSlope12Bat3P

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitRandSlope12at23P	3436.8	15	3466.8	3507.1	.	.	.
FitRandSlope12Bat3P	3432.2	19	3470.2	3521.2	4.63864	4	0.32642

Ch 10b: Piecewise Session Slopes, Linear Burst, Slope12 by Burst1or2

Add Random Linear Slope26 across Bursts for Positive Affect

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10B
Dependent Variable	posaff
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	13
Columns in X	5
Columns in Z per Subject	18
Subjects	108
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2752
Number of Observations Used	2747
Number of Observations Not Used	5

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	6047.08482900
1	3	3430.13119639	0.00444193
2	1	3426.06146404	0.00025732
3	1	3425.84377796	0.00000119
4	1	3425.84281179	0.00000000

Convergence criteria met.

Estimated G Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13	Col14	Col15	Col16	Col17	Col18
1	Intercept	101		0.3400	-0.00314	0.05762
2	burst1	101		-0.00314	0.007254	0.001268
3	slope12	101		0.05762	0.001268	0.03336
4	Intercept	101	1				0.06293	0.009741	-0.00823
5	slope12	101	1				0.009741	0.03173	-0.00133
6	slope26	101	1				-0.00823	-0.00133	0.002761
7	Intercept	101	2							0.06293	0.009741	-0.00823
8	slope12	101	2							0.009741	0.03173	-0.00133
9	slope26	101	2							-0.00823	-0.00133	0.002761
10	Intercept	101	3										0.06293	0.009741	-0.00823
11	slope12	101	3										0.009741	0.03173	-0.00133
12	slope26	101	3										-0.00823	-0.00133	0.002761
13	Intercept	101	4													0.06293	0.009741	-0.00823
14	slope12	101	4													0.009741	0.03173	-0.00133
15	slope26	101	4													-0.00823	-0.00133	0.002761
16	Intercept	101	5																0.06293	0.009741	-0.00823
17	slope12	101	5																0.009741	0.03173	-0.00133
18	slope26	101	5																-0.00823	-0.00133	0.002761

Estimated G Correlation Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13	Col14	Col15	Col16	Col17	Col18
1	Intercept	101		1.0000	-0.06313	0.5410
2	burst1	101		-0.06313	1.0000	0.08152
3	slope12	101		0.5410	0.08152	1.0000
4	Intercept	101	1				1.0000	0.2180	-0.6241
5	slope12	101	1				0.2180	1.0000	-0.1420
6	slope26	101	1				-0.6241	-0.1420	1.0000
7	Intercept	101	2							1.0000	0.2180	-0.6241
8	slope12	101	2							0.2180	1.0000	-0.1420
9	slope26	101	2							-0.6241	-0.1420	1.0000
10	Intercept	101	3										1.0000	0.2180	-0.6241
11	slope12	101	3										0.2180	1.0000	-0.1420
12	slope26	101	3										-0.6241	-0.1420	1.0000
13	Intercept	101	4													1.0000	0.2180	-0.6241
14	slope12	101	4													0.2180	1.0000	-0.1420
15	slope26	101	4													-0.6241	-0.1420	1.0000
16	Intercept	101	5																1.0000	0.2180	-0.6241
17	slope12	101	5																0.2180	1.0000	-0.1420
18	slope26	101	5																-0.6241	-0.1420	1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr Z
UN(1,1)	PersonID	0.3400	0.05254	6.47	<.0001
UN(2,1)	PersonID	-0.00314	0.008027	-0.39	0.6961
UN(2,2)	PersonID	0.007254	0.002156	3.37	0.0004
UN(3,1)	PersonID	0.05762	0.01857	3.10	0.0019
UN(3,2)	PersonID	0.001268	0.003397	0.37	0.7089
UN(3,3)	PersonID	0.03336	0.01162	2.87	0.0020
UN(1,1)	PersonID*burst	0.06293	0.01212	5.19	<.0001
UN(2,1)	PersonID*burst	0.009741	0.01160	0.84	0.4011
UN(2,2)	PersonID*burst	0.03173	0.01997	1.59	0.0560
UN(3,1)	PersonID*burst	-0.00823	0.003280	-2.51	0.0121
UN(3,2)	PersonID*burst	-0.00133	0.003605	-0.37	0.7124
UN(3,3)	PersonID*burst	0.002761	0.001214	2.27	0.0115
Residual		0.1371	0.005243	26.16	<.0001

Fit Statistics
-2 Log Likelihood	3425.8
AIC (Smaller is Better)	3461.8
AICC (Smaller is Better)	3462.1
BIC (Smaller is Better)	3510.1

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
12	2621.24	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
3425.8	18	3461.8	3462.1	3481.4	3510.1	3528.1

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	2.5719	0.06105	117	42.13	<.0001	0.05	2.4510	2.6928
burst1	-0.04546	0.01256	102	-3.62	0.0005	0.05	-0.07037	-0.02055
slope12	-0.01863	0.03502	214	-0.53	0.5953	0.05	-0.08766	0.05040
slope12*b1or2	-0.1926	0.04215	385	-4.57	<.0001	0.05	-0.2755	-0.1098
slope26	0.01720	0.005999	457	2.87	0.0043	0.05	0.005409	0.02899

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	102	13.10	13.10	0.0003	0.0005
slope12	1	214	0.28	0.28	0.5947	0.5953
slope12*b1or2	1	385	20.89	20.89	<.0001	<.0001
slope26	1	457	8.22	8.22	0.0041	0.0043

Likelihood Ratio Test for FitRandSlope12at23P vs. FitRandSlope26at2P

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitRandSlope12at23P	3436.8	15	3466.8	3507.1	.	.	.
FitRandSlope26at2P	3425.8	18	3461.8	3510.1	10.9942	3	0.011757

Eq 10b.13: Piecewise Session Slopes, Linear Burst, Slope12 by Burst1or2

Add Random Linear Slope26 across Persons for Positive Affect

The Mixed Procedure

Model Information
Data Set	WORK.PLOTMEANS
Dependent Variable	posaff
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonID*burst
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	17
Columns in X	5
Columns in Z per Subject	19
Subjects	109
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2782
Number of Observations Used	2747
Number of Observations Not Used	35

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	6047.08482900
1	3	3412.69123999	0.00012713
2	1	3412.58255284	0.00000073
3	1	3412.58195281	0.00000000

Convergence criteria met.

Estimated G Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13	Col14	Col15	Col16	Col17	Col18	Col19
1	Intercept	-99		0.3070	-0.00481	0.03697	0.006251
2	burst1	-99		-0.00481	0.007194	-0.00007	0.000639
3	slope12	-99		0.03697	-0.00007	0.02141	0.002075
4	slope26	-99		0.006251	0.000639	0.002075	0.001322
5	Intercept	-99	1					0.06051	0.01094	-0.00621
6	slope12	-99	1					0.01094	0.03535	-0.00106
7	slope26	-99	1					-0.00621	-0.00106	0.001441
8	Intercept	-99	2								0.06051	0.01094	-0.00621
9	slope12	-99	2								0.01094	0.03535	-0.00106
10	slope26	-99	2								-0.00621	-0.00106	0.001441
11	Intercept	-99	3											0.06051	0.01094	-0.00621
12	slope12	-99	3											0.01094	0.03535	-0.00106
13	slope26	-99	3											-0.00621	-0.00106	0.001441
14	Intercept	-99	4														0.06051	0.01094	-0.00621
15	slope12	-99	4														0.01094	0.03535	-0.00106
16	slope26	-99	4														-0.00621	-0.00106	0.001441
17	Intercept	-99	5																	0.06051	0.01094	-0.00621
18	slope12	-99	5																	0.01094	0.03535	-0.00106
19	slope26	-99	5																	-0.00621	-0.00106	0.001441

Estimated G Correlation Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13	Col14	Col15	Col16	Col17	Col18	Col19
1	Intercept	-99		1.0000	-0.1023	0.4560	0.3103
2	burst1	-99		-0.1023	1.0000	-0.00551	0.2072
3	slope12	-99		0.4560	-0.00551	1.0000	0.3900
4	slope26	-99		0.3103	0.2072	0.3900	1.0000
5	Intercept	-99	1					1.0000	0.2365	-0.6653
6	slope12	-99	1					0.2365	1.0000	-0.1488
7	slope26	-99	1					-0.6653	-0.1488	1.0000
8	Intercept	-99	2								1.0000	0.2365	-0.6653
9	slope12	-99	2								0.2365	1.0000	-0.1488
10	slope26	-99	2								-0.6653	-0.1488	1.0000
11	Intercept	-99	3											1.0000	0.2365	-0.6653
12	slope12	-99	3											0.2365	1.0000	-0.1488
13	slope26	-99	3											-0.6653	-0.1488	1.0000
14	Intercept	-99	4														1.0000	0.2365	-0.6653
15	slope12	-99	4														0.2365	1.0000	-0.1488
16	slope26	-99	4														-0.6653	-0.1488	1.0000
17	Intercept	-99	5																	1.0000	0.2365	-0.6653
18	slope12	-99	5																	0.2365	1.0000	-0.1488
19	slope26	-99	5																	-0.6653	-0.1488	1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr Z
UN(1,1)	PersonID	0.3070	0.05050	6.08	<.0001
UN(2,1)	PersonID	-0.00481	0.007899	-0.61	0.5429
UN(2,2)	PersonID	0.007194	0.002149	3.35	0.0004
UN(3,1)	PersonID	0.03697	0.01814	2.04	0.0415
UN(3,2)	PersonID	-0.00007	0.003406	-0.02	0.9840
UN(3,3)	PersonID	0.02141	0.01203	1.78	0.0376
UN(4,1)	PersonID	0.006251	0.004252	1.47	0.1415
UN(4,2)	PersonID	0.000639	0.000840	0.76	0.4469
UN(4,3)	PersonID	0.002075	0.002144	0.97	0.3332
UN(4,4)	PersonID	0.001322	0.000708	1.87	0.0309
UN(1,1)	PersonID*burst	0.06051	0.01221	4.96	<.0001
UN(2,1)	PersonID*burst	0.01094	0.01225	0.89	0.3720
UN(2,2)	PersonID*burst	0.03535	0.02105	1.68	0.0465
UN(3,1)	PersonID*burst	-0.00621	0.003324	-1.87	0.0616
UN(3,2)	PersonID*burst	-0.00106	0.003799	-0.28	0.7798
UN(3,3)	PersonID*burst	0.001441	0.001258	1.15	0.1260
Residual		0.1371	0.005242	26.16	<.0001

Fit Statistics
-2 Log Likelihood	3412.6
AIC (Smaller is Better)	3456.6
AICC (Smaller is Better)	3457.0
BIC (Smaller is Better)	3515.8

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
16	2634.50	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
3412.6	22	3456.6	3457.0	3480.6	3515.8	3537.8

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	2.5739	0.05847	108	44.02	<.0001	0.05	2.4580	2.6898
burst1	-0.04511	0.01253	102	-3.60	0.0005	0.05	-0.06996	-0.02026
slope12	-0.01580	0.03340	184	-0.47	0.6367	0.05	-0.08171	0.05010
slope12*b1or2	-0.1940	0.04216	385	-4.60	<.0001	0.05	-0.2769	-0.1111
slope26	0.01601	0.006789	101	2.36	0.0203	0.05	0.002541	0.02947

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	102	12.96	12.96	0.0003	0.0005
slope12	1	184	0.22	0.22	0.6361	0.6367
slope12*b1or2	1	385	21.18	21.18	<.0001	<.0001
slope26	1	101	5.56	5.56	0.0184	0.0203

Estimates
Label	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Slope12 at Burst 1 or 2	-0.2098	0.03623	270	-5.79	<.0001	0.05	-0.2811	-0.1385

Likelihood Ratio Test for FitRandSlope26at2P vs. FitRandSlope26at23P

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitRandSlope26at2P	3425.8	18	3461.8	3510.1	.	.	.
FitRandSlope26at23P	3412.6	22	3456.6	3515.8	13.2609	4	0.010069

Total R2 (% Reduction) for PredEmpty3P vs. PredUncP

Name	PredCorr	TotalR2	TotalR2Diff
PredEmpty3P	.	.	.
PredUncP	0.10897	0.011875	.

Predicted Outcomes for Fake People

burst1	slope12	slope26	b1or2	Pred
0	-1	0	1	2.78373
0	0	0	1	2.57392
0	0	1	1	2.58993
0	0	2	1	2.60594
0	0	3	1	2.62195
0	0	4	1	2.63795
1	-1	0	1	2.73862
1	0	0	1	2.52881
1	0	1	1	2.54482
1	0	2	1	2.56083
1	0	3	1	2.57684
1	0	4	1	2.59284
2	-1	0	0	2.49951
2	0	0	0	2.48370
2	0	1	0	2.49971
2	0	2	0	2.51572
2	0	3	0	2.53173
2	0	4	0	2.54773
3	-1	0	0	2.45440
3	0	0	0	2.43859
3	0	1	0	2.45460
3	0	2	0	2.47061
3	0	3	0	2.48661
3	0	4	0	2.50262
4	-1	0	0	2.40929
4	0	0	0	2.39348
4	0	1	0	2.40949
4	0	2	0	2.42550
4	0	3	0	2.44150
4	0	4	0	2.45751

Ch 10b: Final Unconditional Model for Positive Affect

Removing Level-2 Random Effects Variances and Covariances

The Mixed Procedure

Model Information
Data Set	WORK.PLOTMEANS
Dependent Variable	posaff
Covariance Structure	Unstructured
Subject Effect	PersonID
Estimation Method	ML
Residual Variance Method	Profile
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	11
Columns in X	5
Columns in Z per Subject	4
Subjects	109
Max Obs per Subject	30

Number of Observations
Number of Observations Read	2782
Number of Observations Used	2747
Number of Observations Not Used	35

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	6047.08482900
1	2	3564.54158505	0.00008914
2	1	3564.47307380	0.00000031
3	1	3564.47284673	0.00000000

Convergence criteria met.

Estimated G Matrix
Row	Effect	PersonID: Person ID Variable	Col1	Col2	Col3	Col4
1	Intercept	-99	0.3306	-0.01133	0.03579	0.006276
2	burst1	-99	-0.01133	0.01121	-0.00004	0.000635
3	slope12	-99	0.03579	-0.00004	0.01637	0.003456
4	slope26	-99	0.006276	0.000635	0.003456	0.000900

Estimated G Correlation Matrix
Row	Effect	PersonID: Person ID Variable	Col1	Col2	Col3	Col4
1	Intercept	-99	1.0000	-0.1861	0.4866	0.3638
2	burst1	-99	-0.1861	1.0000	-0.00292	0.2000
3	slope12	-99	0.4866	-0.00292	1.0000	0.9004
4	slope26	-99	0.3638	0.2000	0.9004	1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr Z
UN(1,1)	PersonID	0.3306	0.05021	6.58	<.0001
UN(2,1)	PersonID	-0.01133	0.007882	-1.44	0.1507
UN(2,2)	PersonID	0.01121	0.002102	5.33	<.0001
UN(3,1)	PersonID	0.03579	0.01795	1.99	0.0462
UN(3,2)	PersonID	-0.00004	0.003390	-0.01	0.9907
UN(3,3)	PersonID	0.01637	0.01109	1.48	0.0700
UN(4,1)	PersonID	0.006276	0.004217	1.49	0.1366
UN(4,2)	PersonID	0.000635	0.000838	0.76	0.4485
UN(4,3)	PersonID	0.003456	0.001961	1.76	0.0780
UN(4,4)	PersonID	0.000900	0.000667	1.35	0.0885
Residual		0.1715	0.005015	34.19	<.0001

Fit Statistics
-2 Log Likelihood	3564.5
AIC (Smaller is Better)	3596.5
AICC (Smaller is Better)	3596.7
BIC (Smaller is Better)	3639.5

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
10	2482.61	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
3564.5	16	3596.5	3596.7	3613.9	3639.5	3655.5

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
Intercept	2.5723	0.05846	108	44.00	<.0001	0.05	2.4564	2.6881
burst1	-0.04691	0.01253	106	-3.74	0.0003	0.05	-0.07176	-0.02206
slope12	-0.01178	0.03321	191	-0.35	0.7232	0.05	-0.07728	0.05373
slope12*b1or2	-0.2038	0.04198	2436	-4.85	<.0001	0.05	-0.2861	-0.1215
slope26	0.01614	0.006803	102	2.37	0.0195	0.05	0.002649	0.02964

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
burst1	1	106	14.01	14.01	0.0002	0.0003
slope12	1	191	0.13	0.13	0.7229	0.7232
slope12*b1or2	1	2436	23.57	23.57	<.0001	<.0001
slope26	1	102	5.63	5.63	0.0176	0.0195

Likelihood Ratio Test for FitNo2P vs. FitRandSlope26at23P

Name	Neg2LogLike	Parms	AIC	BIC	DevDiff	DFdiff	Pvalue
FitNo2P	3564.5	16	3596.5	3639.5	.	.	.
FitRandSlope26at23P	3412.6	22	3456.6	3515.8	151.891	6	0

Ch 10b: Multivariate Model of Symptoms and Positive Affect

Tricking Univariate Software

The Mixed Procedure

Model Information
Data Set	WORK.CHAPTER10BDOUBLESTACK
Dependent Variable	outcome
Covariance Structure	Unstructured
Subject Effects	PersonID, PersonIDburst, PersonIDburst*session
Estimation Method	ML
Residual Variance Method	None
Fixed Effects SE Method	Model-Based
Degrees of Freedom Method	Satterthwaite

Dimensions
Covariance Parameters	45
Columns in X	12
Columns in Z per Subject	36
Subjects	108
Max Obs per Subject	60

Number of Observations
Number of Observations Read	5504
Number of Observations Used	5499
Number of Observations Not Used	5

Iteration History
Iteration	Evaluations	-2 Log Like	Criterion
0	1	16880.63551090
1	3	10711.20898046	0.01382661
2	1	10706.53593263	0.00063584
3	1	10706.33859582	0.00000189
4	1	10706.33802882	0.00000000

Convergence criteria met.

Estimated R Matrix for PersonIDburstsession 101 1 4
Row	Col1	Col2
1	0.5362	-0.02733
2	-0.02733	0.1371

Estimated R Correlation Matrix for PersonIDburstsession 101 1 4
Row	Col1	Col2
1	1.0000	-0.1008
2	-0.1008	1.0000

Estimated G Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13	Col14	Col15	Col16	Col17	Col18	Col19	Col20	Col21	Col22	Col23	Col24	Col25	Col26	Col27	Col28	Col29	Col30	Col31	Col32	Col33	Col34	Col35	Col36
1	dvS	101		0.9359	0.04402	-0.2192	0.02122	-0.01594	0.002612
2	dvS*burst1	101		0.04402	0.01278	-0.02516	-0.00540	-0.00523	0.001077
3	dvP	101		-0.2192	-0.02516	0.3167	-0.00633	0.03909	0.005007
4	dvP*burst1	101		0.02122	-0.00540	-0.00633	0.007359	-0.00059	0.000772
5	dvP*slope12	101		-0.01594	-0.00523	0.03909	-0.00059	0.02408	0.001422
6	dvP*slope26	101		0.002612	0.001077	0.005007	0.000772	0.001422	0.001305
7	dvS	101	1							0.5110	0.09154	-0.04643	-0.02988	-0.00659	0.003168
8	dvS*slope12	101	1							0.09154	0.2013	0.009048	-0.02052	-0.01674	-0.00111
9	dvS*slope26	101	1							-0.04643	0.009048	0.01197	0.007480	-0.00229	-0.00133
10	dvP	101	1							-0.02988	-0.02052	0.007480	0.05873	0.008163	-0.00590
11	dvP*slope12	101	1							-0.00659	-0.01674	-0.00229	0.008163	0.03276	-0.00057
12	dvP*slope26	101	1							0.003168	-0.00111	-0.00133	-0.00590	-0.00057	0.001405
13	dvS	101	2													0.5110	0.09154	-0.04643	-0.02988	-0.00659	0.003168
14	dvS*slope12	101	2													0.09154	0.2013	0.009048	-0.02052	-0.01674	-0.00111
15	dvS*slope26	101	2													-0.04643	0.009048	0.01197	0.007480	-0.00229	-0.00133
16	dvP	101	2													-0.02988	-0.02052	0.007480	0.05873	0.008163	-0.00590
17	dvP*slope12	101	2													-0.00659	-0.01674	-0.00229	0.008163	0.03276	-0.00057
18	dvP*slope26	101	2													0.003168	-0.00111	-0.00133	-0.00590	-0.00057	0.001405
19	dvS	101	3																			0.5110	0.09154	-0.04643	-0.02988	-0.00659	0.003168
20	dvS*slope12	101	3																			0.09154	0.2013	0.009048	-0.02052	-0.01674	-0.00111
21	dvS*slope26	101	3																			-0.04643	0.009048	0.01197	0.007480	-0.00229	-0.00133
22	dvP	101	3																			-0.02988	-0.02052	0.007480	0.05873	0.008163	-0.00590
23	dvP*slope12	101	3																			-0.00659	-0.01674	-0.00229	0.008163	0.03276	-0.00057
24	dvP*slope26	101	3																			0.003168	-0.00111	-0.00133	-0.00590	-0.00057	0.001405
25	dvS	101	4																									0.5110	0.09154	-0.04643	-0.02988	-0.00659	0.003168
26	dvS*slope12	101	4																									0.09154	0.2013	0.009048	-0.02052	-0.01674	-0.00111
27	dvS*slope26	101	4																									-0.04643	0.009048	0.01197	0.007480	-0.00229	-0.00133
28	dvP	101	4																									-0.02988	-0.02052	0.007480	0.05873	0.008163	-0.00590
29	dvP*slope12	101	4																									-0.00659	-0.01674	-0.00229	0.008163	0.03276	-0.00057
30	dvP*slope26	101	4																									0.003168	-0.00111	-0.00133	-0.00590	-0.00057	0.001405
31	dvS	101	5																															0.5110	0.09154	-0.04643	-0.02988	-0.00659	0.003168
32	dvS*slope12	101	5																															0.09154	0.2013	0.009048	-0.02052	-0.01674	-0.00111
33	dvS*slope26	101	5																															-0.04643	0.009048	0.01197	0.007480	-0.00229	-0.00133
34	dvP	101	5																															-0.02988	-0.02052	0.007480	0.05873	0.008163	-0.00590
35	dvP*slope12	101	5																															-0.00659	-0.01674	-0.00229	0.008163	0.03276	-0.00057
36	dvP*slope26	101	5																															0.003168	-0.00111	-0.00133	-0.00590	-0.00057	0.001405

Estimated G Correlation Matrix
Row	Effect	PersonID: Person ID Variable	burst: Measurement Burst (1-5)	Col1	Col2	Col3	Col4	Col5	Col6	Col7	Col8	Col9	Col10	Col11	Col12	Col13	Col14	Col15	Col16	Col17	Col18	Col19	Col20	Col21	Col22	Col23	Col24	Col25	Col26	Col27	Col28	Col29	Col30	Col31	Col32	Col33	Col34	Col35	Col36
1	dvS	101		1.0000	0.4024	-0.4026	0.2557	-0.1062	0.07474
2	dvS*burst1	101		0.4024	1.0000	-0.3955	-0.5572	-0.2979	0.2637
3	dvP	101		-0.4026	-0.3955	1.0000	-0.1310	0.4476	0.2463
4	dvP*burst1	101		0.2557	-0.5572	-0.1310	1.0000	-0.04449	0.2493
5	dvP*slope12	101		-0.1062	-0.2979	0.4476	-0.04449	1.0000	0.2537
6	dvP*slope26	101		0.07474	0.2637	0.2463	0.2493	0.2537	1.0000
7	dvS	101	1							1.0000	0.2854	-0.5936	-0.1725	-0.05092	0.1182
8	dvS*slope12	101	1							0.2854	1.0000	0.1843	-0.1887	-0.2061	-0.06576
9	dvS*slope26	101	1							-0.5936	0.1843	1.0000	0.2821	-0.1155	-0.3251
10	dvP	101	1							-0.1725	-0.1887	0.2821	1.0000	0.1861	-0.6498
11	dvP*slope12	101	1							-0.05092	-0.2061	-0.1155	0.1861	1.0000	-0.08379
12	dvP*slope26	101	1							0.1182	-0.06576	-0.3251	-0.6498	-0.08379	1.0000
13	dvS	101	2													1.0000	0.2854	-0.5936	-0.1725	-0.05092	0.1182
14	dvS*slope12	101	2													0.2854	1.0000	0.1843	-0.1887	-0.2061	-0.06576
15	dvS*slope26	101	2													-0.5936	0.1843	1.0000	0.2821	-0.1155	-0.3251
16	dvP	101	2													-0.1725	-0.1887	0.2821	1.0000	0.1861	-0.6498
17	dvP*slope12	101	2													-0.05092	-0.2061	-0.1155	0.1861	1.0000	-0.08379
18	dvP*slope26	101	2													0.1182	-0.06576	-0.3251	-0.6498	-0.08379	1.0000
19	dvS	101	3																			1.0000	0.2854	-0.5936	-0.1725	-0.05092	0.1182
20	dvS*slope12	101	3																			0.2854	1.0000	0.1843	-0.1887	-0.2061	-0.06576
21	dvS*slope26	101	3																			-0.5936	0.1843	1.0000	0.2821	-0.1155	-0.3251
22	dvP	101	3																			-0.1725	-0.1887	0.2821	1.0000	0.1861	-0.6498
23	dvP*slope12	101	3																			-0.05092	-0.2061	-0.1155	0.1861	1.0000	-0.08379
24	dvP*slope26	101	3																			0.1182	-0.06576	-0.3251	-0.6498	-0.08379	1.0000
25	dvS	101	4																									1.0000	0.2854	-0.5936	-0.1725	-0.05092	0.1182
26	dvS*slope12	101	4																									0.2854	1.0000	0.1843	-0.1887	-0.2061	-0.06576
27	dvS*slope26	101	4																									-0.5936	0.1843	1.0000	0.2821	-0.1155	-0.3251
28	dvP	101	4																									-0.1725	-0.1887	0.2821	1.0000	0.1861	-0.6498
29	dvP*slope12	101	4																									-0.05092	-0.2061	-0.1155	0.1861	1.0000	-0.08379
30	dvP*slope26	101	4																									0.1182	-0.06576	-0.3251	-0.6498	-0.08379	1.0000
31	dvS	101	5																															1.0000	0.2854	-0.5936	-0.1725	-0.05092	0.1182
32	dvS*slope12	101	5																															0.2854	1.0000	0.1843	-0.1887	-0.2061	-0.06576
33	dvS*slope26	101	5																															-0.5936	0.1843	1.0000	0.2821	-0.1155	-0.3251
34	dvP	101	5																															-0.1725	-0.1887	0.2821	1.0000	0.1861	-0.6498
35	dvP*slope12	101	5																															-0.05092	-0.2061	-0.1155	0.1861	1.0000	-0.08379
36	dvP*slope26	101	5																															0.1182	-0.06576	-0.3251	-0.6498	-0.08379	1.0000

Covariance Parameter Estimates
Cov Parm	Subject	Estimate	Standard Error	Z Value	Pr Z
UN(1,1)	PersonID	0.9359	0.1723	5.43	<.0001
UN(2,1)	PersonID	0.04402	0.03187	1.38	0.1672
UN(2,2)	PersonID	0.01278	0.01019	1.25	0.1048
UN(3,1)	PersonID	-0.2192	0.07011	-3.13	0.0018
UN(3,2)	PersonID	-0.02516	0.01636	-1.54	0.1240
UN(3,3)	PersonID	0.3167	0.05172	6.12	<.0001
UN(4,1)	PersonID	0.02122	0.01499	1.42	0.1569
UN(4,2)	PersonID	-0.00540	0.003375	-1.60	0.1093
UN(4,3)	PersonID	-0.00633	0.008070	-0.78	0.4331
UN(4,4)	PersonID	0.007359	0.002170	3.39	0.0003
UN(5,1)	PersonID	-0.01594	0.03261	-0.49	0.6251
UN(5,2)	PersonID	-0.00523	0.007253	-0.72	0.4712
UN(5,3)	PersonID	0.03909	0.01859	2.10	0.0354
UN(5,4)	PersonID	-0.00059	0.003473	-0.17	0.8646
UN(5,5)	PersonID	0.02408	0.01236	1.95	0.0257
UN(6,1)	PersonID	0.002612	0.007913	0.33	0.7414
UN(6,2)	PersonID	0.001077	0.001742	0.62	0.5363
UN(6,3)	PersonID	0.005007	0.004285	1.17	0.2426
UN(6,4)	PersonID	0.000772	0.000840	0.92	0.3577
UN(6,5)	PersonID	0.001422	0.002174	0.65	0.5130
UN(6,6)	PersonID	0.001305	0.000698	1.87	0.0309
UN(1,1)	PersonID*burst	0.5110	0.06558	7.79	<.0001
UN(2,1)	PersonID*burst	0.09154	0.05274	1.74	0.0826
UN(2,2)	PersonID*burst	0.2013	0.07729	2.60	0.0046
UN(3,1)	PersonID*burst	-0.04643	0.01442	-3.22	0.0013
UN(3,2)	PersonID*burst	0.009048	0.01379	0.66	0.5117
UN(3,3)	PersonID*burst	0.01197	0.004798	2.50	0.0063
UN(4,1)	PersonID*burst	-0.02988	0.01976	-1.51	0.1306
UN(4,2)	PersonID*burst	-0.02052	0.02071	-0.99	0.3217
UN(4,3)	PersonID*burst	0.007480	0.005269	1.42	0.1557
UN(4,4)	PersonID*burst	0.05873	0.01198	4.90	<.0001
UN(5,1)	PersonID*burst	-0.00659	0.02432	-0.27	0.7865
UN(5,2)	PersonID*burst	-0.01674	0.02795	-0.60	0.5493
UN(5,3)	PersonID*burst	-0.00229	0.006428	-0.36	0.7220
UN(5,4)	PersonID*burst	0.008163	0.01200	0.68	0.4962
UN(5,5)	PersonID*burst	0.03276	0.02074	1.58	0.0571
UN(6,1)	PersonID*burst	0.003168	0.006032	0.53	0.5995
UN(6,2)	PersonID*burst	-0.00111	0.006315	-0.18	0.8610
UN(6,3)	PersonID*burst	-0.00133	0.001704	-0.78	0.4338
UN(6,4)	PersonID*burst	-0.00590	0.003283	-1.80	0.0722
UN(6,5)	PersonID*burst	-0.00057	0.003750	-0.15	0.8795
UN(6,6)	PersonID*burst	0.001405	0.001252	1.12	0.1308
UN(1,1)	PersonIDburstsession	0.5362	0.02047	26.19	<.0001
UN(2,1)	PersonIDburstsession	-0.02733	0.007359	-3.71	0.0002
UN(2,2)	PersonIDburstsession	0.1371	0.005242	26.16	<.0001

Fit Statistics
-2 Log Likelihood	10706.3
AIC (Smaller is Better)	10820.3
AICC (Smaller is Better)	10821.6
BIC (Smaller is Better)	10973.2

Null Model Likelihood Ratio Test
DF	Chi-Square	Pr > ChiSq
44	6174.30	<.0001

Information Criteria
Neg2LogLike	Parms	AIC	AICC	HQIC	BIC	CAIC
10706.3	57	10820.3	10821.6	10882.3	10973.2	11030.2

Solution for Fixed Effects
Effect	Estimate	Standard Error	DF	t Value	Pr > \|t\|	Alpha	Lower	Upper
dvS	1.3657	0.1209	165	11.30	<.0001	0.05	1.1270	1.6044
dvP	2.5725	0.05917	107	43.48	<.0001	0.05	2.4552	2.6898
dvS*burst1	0.5180	0.09402	354	5.51	<.0001	0.05	0.3331	0.7029
dvSburst1burst1	-0.1022	0.02299	332	-4.45	<.0001	0.05	-0.1475	-0.05702
dvS*slope12	-0.2270	0.04803	460	-4.73	<.0001	0.05	-0.3214	-0.1326
dvS*slope26	-0.00723	0.02216	496	-0.33	0.7442	0.05	-0.05078	0.03631
dvSburst1slope26	-0.07443	0.02669	460	-2.79	0.0055	0.05	-0.1269	-0.02198
dvSburst1burst1*slope26	0.01877	0.006574	456	2.86	0.0045	0.05	0.005855	0.03169
dvP*burst1	-0.04482	0.01253	101	-3.58	0.0005	0.05	-0.06968	-0.01997
dvP*slope12	-0.01720	0.03364	180	-0.51	0.6097	0.05	-0.08358	0.04918
dvPslope12b1or2	-0.1915	0.04181	382	-4.58	<.0001	0.05	-0.2737	-0.1093
dvP*slope26	0.01648	0.006770	103	2.43	0.0166	0.05	0.003055	0.02991

Type 3 Tests of Fixed Effects
Effect	Num DF	Den DF	Chi-Square	F Value	Pr > ChiSq	Pr > F
dvS	1	165	127.60	127.60	<.0001	<.0001
dvP	1	107	1890.46	1890.46	<.0001	<.0001
dvS*burst1	1	354	30.35	30.35	<.0001	<.0001
dvSburst1burst1	1	332	19.77	19.77	<.0001	<.0001
dvS*slope12	1	460	22.34	22.34	<.0001	<.0001
dvS*slope26	1	496	0.11	0.11	0.7441	0.7442
dvSburst1slope26	1	460	7.78	7.78	0.0053	0.0055
dvSburst1burst1*slope26	1	456	8.16	8.16	0.0043	0.0045
dvP*burst1	1	101	12.80	12.80	0.0003	0.0005
dvP*slope12	1	180	0.26	0.26	0.6091	0.6097
dvPslope12b1or2	1	382	20.98	20.98	<.0001	<.0001
dvP*slope26	1	103	5.93	5.93	0.0149	0.0166