Chapter 8: Descriptive Statistics for Time-Invariant Variables

The MEANS Procedure

Variable Label N Mean Std Dev Minimum Maximum
PMwomen
PMbaseage
PMmood
PMstressor
women: 0=Men, 1=Women
baseage: Age at Baseline
mood: Daily Negative Mood (1-5)
stressor: Daily Stressor (0=No, 1=Yes)
105
105
105
105
0.7333333
80.1296698
1.2060952
0.4495238
0.4443376
6.1050092
0.2668927
0.3362330
0
69.7029432
1.0000000
0
1.0000000
95.3073238
2.5200000
1.0000000


Chapter 8: Descriptive Statistics for Time-Varying Variables

The MEANS Procedure

Variable Label N Mean Std Dev Minimum Maximum
symptoms
mood
stressor
WPmood
WPstressor
symptoms: # Daily Physical Symptoms (0=5)
mood: Daily Negative Mood (1-5)
stressor: Daily Stressor (0=No, 1=Yes)
WPmood: Within-Person Negative Mood (0=PM)
WPstressor: Within-Person Stressors (0=PM)
509
509
509
509
509
1.2730845
1.2031434
0.4518664
0.000471513
0.0039293
1.3243935
0.3799994
0.4981674
0.2729248
0.3671344
0
1.0000000
0
-0.7200000
-0.8000000
5.0000000
3.6000000
1.0000000
1.2800000
0.8000000


Eq 8.1: Conditional Baseline Model
Just Sex and Age in the Model for the Means

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
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 2
Columns in X 4
Columns in Z Per Subject 1
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 1704.13890542  
1 2 1432.58060818 0.00001063
2 1 1432.57794163 0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr > Z
UN(1,1) PersonID 1.0726 0.1667 6.43 <.0001
Residual   0.6152 0.04333 14.20 <.0001

Fit Statistics
-2 Log Likelihood 1432.6
AIC (smaller is better) 1444.6
AICC (smaller is better) 1444.7
BIC (smaller is better) 1460.5

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
1 271.56 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
1432.6 6 1444.6 1444.7 1451.0 1460.5 1466.5

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 1.7127 0.2108 106 8.13 <.0001 0.05 1.2949 2.1306
women -0.5306 0.2451 105 -2.16 0.0327 0.05 -1.0166 -0.04463
age80 0.10000 0.03706 108 2.70 0.0081 0.05 0.02655 0.1735
women*age80 -0.1104 0.04220 107 -2.62 0.0102 0.05 -0.1941 -0.02677

Type 3 Tests of Fixed Effects
Effect Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
women 1 105 4.69 4.69 0.0304 0.0327
age80 1 108 7.28 7.28 0.0070 0.0081
women*age80 1 107 6.85 6.85 0.0089 0.0102


Ch 8: Empty Means, Random Intercept Model for Negative Mood Predictor

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
Dependent Variable mood
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 2
Columns in X 1
Columns in Z Per Subject 1
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 458.47631221  
1 2 373.70453181 0.00001293
2 1 373.70086152 0.00000000

Convergence criteria met.

Estimated V Matrix for PersonID 102
Row Col1 Col2 Col3 Col4 Col5
1 0.1454 0.05239 0.05239 0.05239 0.05239
2 0.05239 0.1454 0.05239 0.05239 0.05239
3 0.05239 0.05239 0.1454 0.05239 0.05239
4 0.05239 0.05239 0.05239 0.1454 0.05239
5 0.05239 0.05239 0.05239 0.05239 0.1454

Estimated V Correlation Matrix for PersonID 102
Row Col1 Col2 Col3 Col4 Col5
1 1.0000 0.3602 0.3602 0.3602 0.3602
2 0.3602 1.0000 0.3602 0.3602 0.3602
3 0.3602 0.3602 1.0000 0.3602 0.3602
4 0.3602 0.3602 0.3602 1.0000 0.3602
5 0.3602 0.3602 0.3602 0.3602 1.0000

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr > Z
UN(1,1) PersonID 0.05239 0.01010 5.19 <.0001
Residual   0.09305 0.006563 14.18 <.0001

Fit Statistics
-2 Log Likelihood 373.7
AIC (smaller is better) 379.7
AICC (smaller is better) 379.7
BIC (smaller is better) 387.7

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
1 84.78 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
373.7 3 379.7 379.7 382.9 387.7 390.7

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 1.2044 0.02614 103 46.07 <.0001 0.05 1.1525 1.2562


Eq 8.3: Adding BP and WP Effects of Negative Mood to the Model for the Means
Using Person-Mean-Centering for Negative Mood

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
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 2
Columns in X 6
Columns in Z Per Subject 1
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 1618.11646622  
1 2 1405.68112526 0.00003345
2 1 1405.67313585 0.00000002
3 1 1405.67313117 0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr > Z
UN(1,1) PersonID 0.8162 0.1314 6.21 <.0001
Residual   0.6127 0.04317 14.19 <.0001

Fit Statistics
-2 Log Likelihood 1405.7
AIC (smaller is better) 1421.7
AICC (smaller is better) 1422.0
BIC (smaller is better) 1442.9

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
1 212.44 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
1405.7 8 1421.7 1422.0 1430.3 1442.9 1450.9

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 3.2655 0.3458 106 9.44 <.0001 0.05 2.5799 3.9511
women -0.5181 0.2175 105 -2.38 0.0190 0.05 -0.9494 -0.08688
age80 0.06690 0.03349 108 2.00 0.0483 0.05 0.000507 0.1333
women*age80 -0.09176 0.03764 107 -2.44 0.0164 0.05 -0.1664 -0.01715
PMmood2 1.9701 0.3687 105 5.34 <.0001 0.05 1.2390 2.7012
WPmood 0.1591 0.1277 404 1.25 0.2136 0.05 -0.09197 0.4102

Type 3 Tests of Fixed Effects
Effect Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
women 1 105 5.67 5.67 0.0172 0.0190
age80 1 108 3.99 3.99 0.0458 0.0483
women*age80 1 107 5.94 5.94 0.0148 0.0164
PMmood2 1 105 28.55 28.55 <.0001 <.0001
WPmood 1 404 1.55 1.55 0.2129 0.2136

Estimates
Label Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Age Slope for Men 0.06690 0.03349 108 2.00 0.0483 0.05 0.000507 0.1333
Age Slope for Women -0.02486 0.01810 104 -1.37 0.1725 0.05 -0.06076 0.01103
Contextual Negative Mood Effect 1.8110 0.3910 132 4.63 <.0001 0.05 1.0376 2.5844
Predicted Symptoms for PMmood=2 WPmood=-1 3.1064 0.3688 136 8.42 <.0001 0.05 2.3771 3.8356
Predicted Symptoms for PMmood=2 WPmood=0 3.2655 0.3458 106 9.44 <.0001 0.05 2.5799 3.9511
Predicted Symptoms for PMmood=2 WPmood=1 3.4246 0.3685 136 9.29 <.0001 0.05 2.6958 4.1533
Predicted Symptoms for PMmood=3 WPmood=-1 5.0765 0.6979 113 7.27 <.0001 0.05 3.6939 6.4591
Predicted Symptoms for PMmood=3 WPmood=0 5.2356 0.6856 105 7.64 <.0001 0.05 3.8763 6.5949
Predicted Symptoms for PMmood=3 WPmood=1 5.3947 0.6969 112 7.74 <.0001 0.05 4.0140 6.7754
Predicted Symptoms for PMmood=1 WPmood=0 1.2954 0.2027 105 6.39 <.0001 0.05 0.8936 1.6972
Predicted Symptoms for PMmood=2 WPmood=0 3.2655 0.3458 106 9.44 <.0001 0.05 2.5799 3.9511
Predicted Symptoms for PMmood=3 WPmood=0 5.2356 0.6856 105 7.64 <.0001 0.05 3.8763 6.5949
Predicted Symptoms for PMmood=4 WPmood=0 7.2057 1.0452 105 6.89 <.0001 0.05 5.1333 9.2780

Contrasts
Label Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
Multivariate Test of BP and WP Negative Mood Fixed Effects 2 166 30.18 15.09 <.0001 <.0001


Likelihood Ratio Test for FitSexAge vs. FitBPWPMood

Name Neg2LogLike Parms AIC BIC DevDiff DFdiff Pvalue
FitSexAge 1432.6 6 1444.6 1460.5 . . .
FitBPWPMood 1405.7 8 1421.7 1442.9 26.9048 2 .000001438


PsuedoR2 (% Reduction) for CovSexAge vs. CovBPWPMood

Name CovParm Subject Estimate StdErr ZValue ProbZ PseudoR2
CovSexAge UN(1,1) PersonID 1.0726 0.1667 6.43 <.0001 .
CovSexAge Residual   0.6152 0.04333 14.20 <.0001 .
CovBPWPMood UN(1,1) PersonID 0.8162 0.1314 6.21 <.0001 0.23911
CovBPWPMood Residual   0.6127 0.04317 14.19 <.0001 0.00401


Total R2 (% Reduction) for PredSexAge vs. PredBPWPMood

Name PredCorr TotalR2 TotalR2Diff
PredSexAge 0.22012 0.04845 .
PredBPWPMood 0.44243 0.19574 0.14729


Eq 8.5: Adding Smushed Effect of Negative Mood to the Model for the Means
Using Grand-Mean-Centering for Negative Mood

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
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 2
Columns in X 5
Columns in Z Per Subject 1
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 1659.95088988  
1 2 1425.81243668 0.00121733
2 1 1425.48882771 0.00002421
3 1 1425.48281288 0.00000001
4 1 1425.48281020 0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr > Z
UN(1,1) PersonID 0.9962 0.1585 6.29 <.0001
Residual   0.6149 0.04347 14.14 <.0001

Fit Statistics
-2 Log Likelihood 1425.5
AIC (smaller is better) 1439.5
AICC (smaller is better) 1439.7
BIC (smaller is better) 1458.1

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
1 234.47 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
1425.5 7 1439.5 1439.7 1447.0 1458.1 1465.1

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 1.9756 0.2261 148 8.74 <.0001 0.05 1.5289 2.4224
women -0.5324 0.2372 103 -2.24 0.0270 0.05 -1.0029 -0.06184
age80 0.09535 0.03591 105 2.65 0.0092 0.05 0.02414 0.1666
women*age80 -0.1083 0.04086 104 -2.65 0.0093 0.05 -0.1893 -0.02731
mood2 0.3295 0.1217 472 2.71 0.0070 0.05 0.09029 0.5687

Type 3 Tests of Fixed Effects
Effect Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
women 1 103 5.04 5.04 0.0248 0.0270
age80 1 105 7.05 7.05 0.0079 0.0092
women*age80 1 104 7.03 7.03 0.0080 0.0093
mood2 1 472 7.33 7.33 0.0068 0.0070

Estimates
Label Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Age Slope for Men 0.09535 0.03591 105 2.65 0.0092 0.05 0.02414 0.1666
Age Slope for Women -0.01298 0.01956 101 -0.66 0.5086 0.05 -0.05177 0.02582


PsuedoR2 (% Reduction) for CovSexAge vs. CovSmushMood

Name CovParm Subject Estimate StdErr ZValue ProbZ PseudoR2
CovSexAge UN(1,1) PersonID 1.0726 0.1667 6.43 <.0001 .
CovSexAge Residual   0.6152 0.04333 14.20 <.0001 .
CovSmushMood UN(1,1) PersonID 0.9962 0.1585 6.29 <.0001 0.071222
CovSmushMood Residual   0.6149 0.04347 14.14 <.0001 0.000468


Eq 8.7: Adding a Contextual Effect of Negative Mood to the Model for the Means
Using Person-Mean-Centering for Negative Mood

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
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 2
Columns in X 6
Columns in Z Per Subject 1
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 1618.11646622  
1 2 1405.68112526 0.00003345
2 1 1405.67313585 0.00000002
3 1 1405.67313117 0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr > Z
UN(1,1) PersonID 0.8162 0.1314 6.21 <.0001
Residual   0.6127 0.04317 14.19 <.0001

Fit Statistics
-2 Log Likelihood 1405.7
AIC (smaller is better) 1421.7
AICC (smaller is better) 1422.0
BIC (smaller is better) 1442.9

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
1 212.44 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
1405.7 8 1421.7 1422.0 1430.3 1442.9 1450.9

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 3.2655 0.3458 106 9.44 <.0001 0.05 2.5799 3.9511
women -0.5181 0.2175 105 -2.38 0.0190 0.05 -0.9494 -0.08688
age80 0.06690 0.03349 108 2.00 0.0483 0.05 0.000507 0.1333
women*age80 -0.09176 0.03764 107 -2.44 0.0164 0.05 -0.1664 -0.01715
mood2 0.1591 0.1277 404 1.25 0.2136 0.05 -0.09197 0.4102
PMmood2 1.8110 0.3910 132 4.63 <.0001 0.05 1.0376 2.5844

Type 3 Tests of Fixed Effects
Effect Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
women 1 105 5.67 5.67 0.0172 0.0190
age80 1 108 3.99 3.99 0.0458 0.0483
women*age80 1 107 5.94 5.94 0.0148 0.0164
mood2 1 404 1.55 1.55 0.2129 0.2136
PMmood2 1 132 21.45 21.45 <.0001 <.0001

Estimates
Label Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Age Slope for Men 0.06690 0.03349 108 2.00 0.0483 0.05 0.000507 0.1333
Age Slope for Women -0.02486 0.01810 104 -1.37 0.1725 0.05 -0.06076 0.01103
Between-Person Negative Mood Effect 1.9701 0.3687 105 5.34 <.0001 0.05 1.2390 2.7012


PsuedoR2 (% Reduction) for CovSmushMood vs. CovBPWPMood

Name CovParm Subject Estimate StdErr ZValue ProbZ PseudoR2
CovSmushMood UN(1,1) PersonID 0.9962 0.1585 6.29 <.0001 .
CovSmushMood Residual   0.6149 0.04347 14.14 <.0001 .
CovBPWPMood UN(1,1) PersonID 0.8162 0.1314 6.21 <.0001 0.18076
CovBPWPMood Residual   0.6127 0.04317 14.19 <.0001 0.00355


PsuedoR2 (% Reduction) for CovSexAge vs. CovBPWPMood

Name CovParm Subject Estimate StdErr ZValue ProbZ PseudoR2
CovSexAge UN(1,1) PersonID 1.0726 0.1667 6.43 <.0001 .
CovSexAge Residual   0.6152 0.04333 14.20 <.0001 .
CovBPWPMood UN(1,1) PersonID 0.8162 0.1314 6.21 <.0001 0.23911
CovBPWPMood Residual   0.6127 0.04317 14.19 <.0001 0.00401


Total R2 (% Reduction) for PredSexAge vs. PredBPWPMood2

Name PredCorr TotalR2 TotalR2Diff
PredSexAge 0.22012 0.04845 .
PredBPWPMood2 0.44243 0.19574 0.14729


Eq 8.9: Adding a Random Effect of Negative Mood to the Model for the Variance
Using Person-Mean-Centering for Negative Mood

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
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 6
Columns in Z Per Subject 2
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 1618.11646622  
1 3 1404.16836625 0.00007589
2 1 1404.15010953 0.00000014
3 1 1404.15007702 0.00000000

Convergence criteria met.

Estimated G Matrix
Row Effect PersonID:
Person ID
variable		 Col1 Col2
1 Intercept 102 0.8172 0.1326
2 WPmood 102 0.1326 0.06233

Estimated G Correlation Matrix
Row Effect PersonID:
Person ID
variable		 Col1 Col2
1 Intercept 102 1.0000 0.5875
2 WPmood 102 0.5875 1.0000

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr Z
UN(1,1) PersonID 0.8172 0.1315 6.22 <.0001
UN(2,1) PersonID 0.1326 0.1355 0.98 0.3280
UN(2,2) PersonID 0.06233 0.1403 0.44 0.3284
Residual   0.6066 0.04458 13.61 <.0001

Fit Statistics
-2 Log Likelihood 1404.2
AIC (smaller is better) 1424.2
AICC (smaller is better) 1424.6
BIC (smaller is better) 1450.7

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
3 213.97 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
1404.2 10 1424.2 1424.6 1434.9 1450.7 1460.7

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 3.2725 0.3445 106 9.50 <.0001 0.05 2.5895 3.9555
women -0.5361 0.2162 105 -2.48 0.0148 0.05 -0.9649 -0.1074
age80 0.06633 0.03320 105 2.00 0.0483 0.05 0.000507 0.1322
women*age80 -0.09271 0.03733 105 -2.48 0.0146 0.05 -0.1667 -0.01869
PMmood2 1.9611 0.3675 105 5.34 <.0001 0.05 1.2324 2.6897
WPmood 0.1589 0.1350 28.4 1.18 0.2489 0.05 -0.1174 0.4351

Type 3 Tests of Fixed Effects
Effect Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
women 1 105 6.15 6.15 0.0132 0.0148
age80 1 105 3.99 3.99 0.0457 0.0483
women*age80 1 105 6.17 6.17 0.0130 0.0146
PMmood2 1 105 28.48 28.48 <.0001 <.0001
WPmood 1 28.4 1.39 1.39 0.2392 0.2489


Likelihood Ratio Test for FitBPWPMood vs. FitRandPMC

Name Neg2LogLike Parms AIC BIC DevDiff DFdiff Pvalue
FitBPWPMood 1405.7 8 1421.7 1442.9 . . .
FitRandPMC 1404.2 10 1424.2 1450.7 1.52305 2 0.46695


Eq 8.9: Adding a Random Effect of Negative Mood to the Model for the Variance
Using Grand-Mean-Centering for Negative Mood

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
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 6
Columns in Z Per Subject 2
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 1618.11646622  
1 2 1403.40482038 0.00000619
2 1 1403.40334602 0.00000000

Convergence criteria met.

Estimated G Matrix
Row Effect PersonID:
Person ID
variable		 Col1 Col2
1 Intercept 102 1.0996 0.2071
2 mood2 102 0.2071 0.06260

Estimated G Correlation Matrix
Row Effect PersonID:
Person ID
variable		 Col1 Col2
1 Intercept 102 1.0000 0.7895
2 mood2 102 0.7895 1.0000

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr Z
UN(1,1) PersonID 1.0996 0.2844 3.87 <.0001
UN(2,1) PersonID 0.2071 0.1692 1.22 0.2208
UN(2,2) PersonID 0.06260 0.1379 0.45 0.3249
Residual   0.6076 0.04459 13.63 <.0001

Fit Statistics
-2 Log Likelihood 1403.4
AIC (smaller is better) 1423.4
AICC (smaller is better) 1423.8
BIC (smaller is better) 1449.9

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
3 214.71 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
1403.4 10 1423.4 1423.8 1434.2 1449.9 1459.9

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 3.3666 0.3693 80.8 9.12 <.0001 0.05 2.6318 4.1014
women -0.5158 0.2152 104 -2.40 0.0183 0.05 -0.9426 -0.08896
age80 0.06202 0.03349 110 1.85 0.0668 0.05 -0.00436 0.1284
women*age80 -0.08701 0.03763 109 -2.31 0.0227 0.05 -0.1616 -0.01242
mood2 0.1711 0.1347 29.6 1.27 0.2139 0.05 -0.1042 0.4464
PMmood2 1.9276 0.3966 133 4.86 <.0001 0.05 1.1430 2.7121

Type 3 Tests of Fixed Effects
Effect Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
women 1 104 5.74 5.74 0.0166 0.0183
age80 1 110 3.43 3.43 0.0641 0.0668
women*age80 1 109 5.34 5.34 0.0208 0.0227
mood2 1 29.6 1.61 1.61 0.2040 0.2139
PMmood2 1 133 23.62 23.62 <.0001 <.0001


Likelihood Ratio Test for FitBPWPMood vs. FitRandGMC

Name Neg2LogLike Parms AIC BIC DevDiff DFdiff Pvalue
FitBPWPMood 1405.7 8 1421.7 1442.9 . . .
FitRandGMC 1403.4 10 1423.4 1449.9 2.26979 2 0.32146


Eq 8.10: Adding Contextual and WP Effects of Stressors to the Model for the Means
Using Person-Mean-Centering for Negative Mood, Grand-Mean-Centering for Stressors

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
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 2
Columns in X 8
Columns in Z Per Subject 1
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 1580.56060061  
1 2 1392.81302475 0.00002337
2 1 1392.80761036 0.00000001

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr > Z
UN(1,1) PersonID 0.7134 0.1172 6.09 <.0001
Residual   0.6116 0.04310 14.19 <.0001

Fit Statistics
-2 Log Likelihood 1392.8
AIC (smaller is better) 1412.8
AICC (smaller is better) 1413.2
BIC (smaller is better) 1439.3

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
1 187.75 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
1392.8 10 1412.8 1413.2 1423.6 1439.3 1449.3

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 2.7837 0.3518 110 7.91 <.0001 0.05 2.0864 3.4810
women -0.5125 0.2054 105 -2.50 0.0141 0.05 -0.9197 -0.1053
age80 0.07288 0.03170 108 2.30 0.0234 0.05 0.01004 0.1357
women*age80 -0.09362 0.03556 107 -2.63 0.0097 0.05 -0.1641 -0.02312
PMmood2 1.4768 0.3742 105 3.95 0.0001 0.05 0.7348 2.2187
WPmood 0.1339 0.1305 404 1.03 0.3056 0.05 -0.1227 0.3905
PMstressor40 0.9432 0.3031 128 3.11 0.0023 0.05 0.3435 1.5430
stressor 0.08555 0.09691 403 0.88 0.3779 0.05 -0.1050 0.2761

Type 3 Tests of Fixed Effects
Effect Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
women 1 105 6.23 6.23 0.0126 0.0141
age80 1 108 5.29 5.29 0.0215 0.0234
women*age80 1 107 6.93 6.93 0.0085 0.0097
PMmood2 1 105 15.58 15.58 <.0001 0.0001
WPmood 1 404 1.05 1.05 0.3050 0.3056
PMstressor40 1 128 9.68 9.68 0.0019 0.0023
stressor 1 403 0.78 0.78 0.3774 0.3779

Estimates
Label Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept for Women 2.2712 0.3230 109 7.03 <.0001 0.05 1.6310 2.9114
Age Slope for Women -0.02074 0.01712 103 -1.21 0.2285 0.05 -0.05469 0.01321
Contextual Negative Mood Effect 1.3429 0.3969 133 3.38 0.0009 0.05 0.5578 2.1280
Between-Person Stressor Effect 1.0288 0.2874 104 3.58 0.0005 0.05 0.4589 1.5986
Contextual Negative Mood Effect Per Day 0.2954 0.07484 105 3.95 0.0001 0.05 0.1470 0.4437

Contrasts
Label Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
Multivariate Test of Stressor Fixed Effects 2 210 13.59 6.79 0.0011 0.0014


Likelihood Ratio Test for FitBPWPMood vs. FitBPWPStressor

Name Neg2LogLike Parms AIC BIC DevDiff DFdiff Pvalue
FitBPWPMood 1405.7 8 1421.7 1442.9 . . .
FitBPWPStressor 1392.8 10 1412.8 1439.3 12.8655 2 .001608006


Likelihood Ratio Test for FitSexAge vs. FitBPWPStressor

Name Neg2LogLike Parms AIC BIC DevDiff DFdiff Pvalue
FitSexAge 1432.6 6 1444.6 1460.5 . . .
FitBPWPStressor 1392.8 10 1412.8 1439.3 39.7703 4 4.8286E-8


PsuedoR2 (% Reduction) for CovBPWPMood vs. CovBPWPStressor

Name CovParm Subject Estimate StdErr ZValue ProbZ PseudoR2
CovBPWPMood UN(1,1) PersonID 0.8162 0.1314 6.21 <.0001 .
CovBPWPMood Residual   0.6127 0.04317 14.19 <.0001 .
CovBPWPStressor UN(1,1) PersonID 0.7134 0.1172 6.09 <.0001 0.12594
CovBPWPStressor Residual   0.6116 0.04310 14.19 <.0001 0.00181


Total R2 (% Reduction) for PredBPWPMood vs. PredBPWPStressor

Name PredCorr TotalR2 TotalR2Diff
PredBPWPMood 0.44243 0.19574 .
PredBPWPStressor 0.50294 0.25295 0.057211


Total R2 (% Reduction) for PredSexAge vs. PredBPWPStressor

Name PredCorr TotalR2 TotalR2Diff
PredSexAge 0.22012 0.04845 .
PredBPWPStressor 0.50294 0.25295 0.20450


Ch 8: Adding Random WP Effect of Stressors to the Model for the Variance
Using Person-Mean-Centering for Negative Mood, Grand-Mean-Centering for Stressors

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
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 8
Columns in Z Per Subject 2
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 1580.56060061  
1 4 1387.37982914 0.03293305
2 2 1383.94635297 0.00258035
3 1 1383.29482264 0.00012855
4 1 1383.26504308 0.00000038
5 1 1383.26495826 0.00000000

Convergence criteria met.

Estimated G Matrix
Row Effect PersonID:
Person ID
variable		 Col1 Col2
1 Intercept 102 0.4645 0.2480
2 stressor 102 0.2480  

Estimated G Correlation Matrix
Row Effect PersonID:
Person ID
variable		 Col1 Col2
1 Intercept 102 1.0000  
2 stressor 102   1.0000

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr Z
UN(1,1) PersonID 0.4645 0.1059 4.39 <.0001
UN(2,1) PersonID 0.2480 0.07889 3.14 0.0017
UN(2,2) PersonID 0 . . .
Residual   0.6183 0.04384 14.10 <.0001

Fit Statistics
-2 Log Likelihood 1383.3
AIC (smaller is better) 1405.3
AICC (smaller is better) 1405.8
BIC (smaller is better) 1434.5

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
2 197.30 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
1383.3 11 1405.3 1405.8 1417.1 1434.5 1445.5

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 2.7789 0.3455 116 8.04 <.0001 0.05 2.0946 3.4632
women -0.3617 0.1910 96 -1.89 0.0613 0.05 -0.7409 0.01753
age80 0.06903 0.02999 105 2.30 0.0233 0.05 0.009573 0.1285
women*age80 -0.09119 0.03348 102 -2.72 0.0076 0.05 -0.1576 -0.02478
PMmood2 1.6044 0.3751 115 4.28 <.0001 0.05 0.8615 2.3474
WPmood 0.1412 0.1298 399 1.09 0.2773 0.05 -0.1140 0.3964
PMstressor40 0.9302 0.2911 124 3.20 0.0018 0.05 0.3541 1.5063
stressor 0.07724 0.09521 372 0.81 0.4177 0.05 -0.1100 0.2645

Type 3 Tests of Fixed Effects
Effect Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
women 1 96 3.58 3.58 0.0583 0.0613
age80 1 105 5.30 5.30 0.0213 0.0233
women*age80 1 102 7.42 7.42 0.0065 0.0076
PMmood2 1 115 18.30 18.30 <.0001 <.0001
WPmood 1 399 1.18 1.18 0.2766 0.2773
PMstressor40 1 124 10.21 10.21 0.0014 0.0018
stressor 1 372 0.66 0.66 0.4172 0.4177


Likelihood Ratio Test for FitBPWPStressor vs. FitBPWPStressorR

Name Neg2LogLike Parms AIC BIC DevDiff DFdiff Pvalue
FitBPWPStressor 1392.8 10 1412.8 1439.3 . . .
FitBPWPStressorR 1383.3 11 1405.3 1434.5 9.54265 1 .002007515


Eq 8.11: Adding 4 Sex*Negative Mood and Sex*Stressors Interactions to the Model for the Means
Using Person-Mean-Centering for Negative Mood, Grand-Mean-Centering for Stressors

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
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 2
Columns in X 12
Columns in Z Per Subject 1
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 1560.79757010  
1 2 1383.86614716 0.00001284
2 1 1383.86324021 0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr > Z
UN(1,1) PersonID 0.6629 0.1099 6.03 <.0001
Residual   0.6081 0.04284 14.19 <.0001

Fit Statistics
-2 Log Likelihood 1383.9
AIC (smaller is better) 1411.9
AICC (smaller is better) 1412.7
BIC (smaller is better) 1449.0

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
1 176.93 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
1383.9 14 1411.9 1412.7 1426.9 1449.0 1463.0

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 2.9158 0.7655 112 3.81 0.0002 0.05 1.3990 4.4326
women -0.6744 0.8371 111 -0.81 0.4222 0.05 -2.3331 0.9844
age80 0.06415 0.03359 106 1.91 0.0589 0.05 -0.00245 0.1307
women*age80 -0.08435 0.03748 106 -2.25 0.0265 0.05 -0.1587 -0.01003
PMmood2 1.8143 0.9206 109 1.97 0.0513 0.05 -0.01023 3.6388
WPmood -0.1555 0.2729 407 -0.57 0.5691 0.05 -0.6921 0.3810
PMstressor40 1.9850 0.6666 123 2.98 0.0035 0.05 0.6655 3.3044
stressor 0.2435 0.1721 404 1.41 0.1579 0.05 -0.09488 0.5819
women*PMmood2 -0.4318 1.0017 108 -0.43 0.6672 0.05 -2.4173 1.5536
women*WPmood 0.3855 0.3107 406 1.24 0.2153 0.05 -0.2252 0.9962
women*PMstressor40 -1.2770 0.7441 125 -1.72 0.0886 0.05 -2.7496 0.1957
women*stressor -0.2336 0.2080 404 -1.12 0.2621 0.05 -0.6426 0.1753

Type 3 Tests of Fixed Effects
Effect Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
women 1 111 0.65 0.65 0.4205 0.4222
age80 1 106 3.65 3.65 0.0562 0.0589
women*age80 1 106 5.06 5.06 0.0244 0.0265
PMmood2 1 109 3.88 3.88 0.0487 0.0513
WPmood 1 407 0.32 0.32 0.5688 0.5691
PMstressor40 1 123 8.87 8.87 0.0029 0.0035
stressor 1 404 2.00 2.00 0.1572 0.1579
women*PMmood2 1 108 0.19 0.19 0.6664 0.6672
women*WPmood 1 406 1.54 1.54 0.2146 0.2153
women*PMstressor40 1 125 2.95 2.95 0.0861 0.0886
women*stressor 1 404 1.26 1.26 0.2614 0.2621

Estimates
Label Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept: Men 2.9158 0.7655 112 3.81 0.0002 0.05 1.3990 4.4326
Intercept: Women 2.2415 0.3388 110 6.62 <.0001 0.05 1.5700 2.9129
Intercept: Sex Diff -0.6744 0.8371 111 -0.81 0.4222 0.05 -2.3331 0.9844
Age Slope: Men 0.06415 0.03359 106 1.91 0.0589 0.05 -0.00245 0.1307
Age Slope: Women -0.02020 0.01663 104 -1.21 0.2273 0.05 -0.05318 0.01278
Age Slope: Sex Diff -0.08435 0.03748 106 -2.25 0.0265 0.05 -0.1587 -0.01003
BP Negative Mood: Men 1.8143 0.9206 109 1.97 0.0513 0.05 -0.01023 3.6388
BP Negative Mood: Women 1.3825 0.3949 105 3.50 0.0007 0.05 0.5995 2.1654
BP Negative Mood: Sex Diff -0.4318 1.0017 108 -0.43 0.6672 0.05 -2.4173 1.5536
Contextual Negative Mood: Men 1.9698 0.9533 125 2.07 0.0409 0.05 0.08323 3.8564
Contextual Negative Mood: Women 1.1525 0.4235 138 2.72 0.0073 0.05 0.3152 1.9898
Contextual Negative Mood: Sex Diff -0.8174 1.0431 127 -0.78 0.4347 0.05 -2.8814 1.2467
WP Negative Mood: Men -0.1555 0.2729 407 -0.57 0.5691 0.05 -0.6921 0.3810
WP Negative Mood: Women 0.2300 0.1484 403 1.55 0.1220 0.05 -0.06175 0.5217
WP Negative Mood: Sex Diff 0.3855 0.3107 406 1.24 0.2153 0.05 -0.2252 0.9962
BP Stressors: Men 2.2285 0.6435 107 3.46 0.0008 0.05 0.9528 3.5041
BP Stressors: Women 0.7179 0.3097 104 2.32 0.0224 0.05 0.1037 1.3321
BP Stressors: Sex Diff -1.5106 0.7141 106 -2.12 0.0367 0.05 -2.9264 -0.09477
Contextual Stressors: Men 1.9850 0.6666 123 2.98 0.0035 0.05 0.6655 3.3044
Contextual Stressors: Women 0.7080 0.3307 134 2.14 0.0341 0.05 0.05391 1.3621
Contextual Stressors: Sex Diff -1.2770 0.7441 125 -1.72 0.0886 0.05 -2.7496 0.1957
WP Stressors: Men 0.2435 0.1721 404 1.41 0.1579 0.05 -0.09488 0.5819
WP Stressors: Women 0.009913 0.1168 403 0.08 0.9324 0.05 -0.2197 0.2395
WP Stressors: Sex Diff -0.2336 0.2080 404 -1.12 0.2621 0.05 -0.6426 0.1753
Contextual Stressors per Day 0.3970 0.1333 123 2.98 0.0035 0.05 0.1331 0.6609

Contrasts
Label Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
Multivariate Test of 4 Sex Interactions 4 188 9.16 2.29 0.0572 0.0613


Likelihood Ratio Test for FitBPWPStressor vs. FitSex4

Name Neg2LogLike Parms AIC BIC DevDiff DFdiff Pvalue
FitBPWPStressor 1392.8 10 1412.8 1439.3 . . .
FitSex4 1383.9 14 1411.9 1449.0 8.94437 4 0.062505


Total R2 (% Reduction) for PredBPWPStressor vs. PredSex4

Name PredCorr TotalR2 TotalR2Diff
PredBPWPStressor 0.50294 0.25295 .
PredSex4 0.53024 0.28116 0.028204


Eq 8.11reduced: Adding Only 2 Sex*Stressors Interactions to the Model for the Means
Using Person-Mean-Centering for Negative Mood, Grand-Mean-Centering for Stressors

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
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 2
Columns in X 10
Columns in Z Per Subject 1
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 1561.79245955  
1 2 1385.61059487 0.00001607
2 1 1385.60693767 0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr > Z
UN(1,1) PersonID 0.6646 0.1103 6.02 <.0001
Residual   0.6103 0.04300 14.19 <.0001

Fit Statistics
-2 Log Likelihood 1385.6
AIC (smaller is better) 1409.6
AICC (smaller is better) 1410.2
BIC (smaller is better) 1441.5

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
1 176.19 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
1385.6 12 1409.6 1410.2 1422.5 1441.5 1453.5

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 2.6416 0.3479 116 7.59 <.0001 0.05 1.9526 3.3307
women -0.3471 0.2189 144 -1.59 0.1150 0.05 -0.7798 0.08561
age80 0.07083 0.03079 108 2.30 0.0233 0.05 0.009801 0.1319
women*age80 -0.09155 0.03453 107 -2.65 0.0092 0.05 -0.1600 -0.02309
PMmood2 1.4560 0.3634 105 4.01 0.0001 0.05 0.7356 2.1764
WPmood 0.1411 0.1306 404 1.08 0.2806 0.05 -0.1156 0.3978
PMstressor40 2.1285 0.6100 123 3.49 0.0007 0.05 0.9211 3.3360
stressor 0.2155 0.1710 404 1.26 0.2084 0.05 -0.1207 0.5516
women*PMstressor40 -1.4562 0.6757 126 -2.16 0.0331 0.05 -2.7934 -0.1190
women*stressor -0.1894 0.2054 404 -0.92 0.3569 0.05 -0.5931 0.2143

Type 3 Tests of Fixed Effects
Effect Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
women 1 144 2.51 2.51 0.1128 0.1150
age80 1 108 5.29 5.29 0.0214 0.0233
women*age80 1 107 7.03 7.03 0.0080 0.0092
PMmood2 1 105 16.06 16.06 <.0001 0.0001
WPmood 1 404 1.17 1.17 0.2800 0.2806
PMstressor40 1 123 12.17 12.17 0.0005 0.0007
stressor 1 404 1.59 1.59 0.2077 0.2084
women*PMstressor40 1 126 4.64 4.64 0.0312 0.0331
women*stressor 1 404 0.85 0.85 0.3564 0.3569

Contrasts
Label Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
Multivariate Test of 2 Sex Interactions 2 206 7.39 3.70 0.0248 0.0265


Likelihood Ratio Test for FitBPWPStressor vs. FitSex2

Name Neg2LogLike Parms AIC BIC DevDiff DFdiff Pvalue
FitBPWPStressor 1392.8 10 1412.8 1439.3 . . .
FitSex2 1385.6 12 1409.6 1441.5 7.20067 2 0.027315


Total R2 (% Reduction) for PredBPWPStressor vs. PredSex2

Name PredCorr TotalR2 TotalR2Diff
PredBPWPStressor 0.50294 0.25295 .
PredSex2 0.52917 0.28002 0.027068


Eq 8.12: Adding 4 Negative Mood*Stressors Interactions to the Model for the Means
Using Person-Mean-Centering for Negative Mood, Grand-Mean-Centering for Stressors

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
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 2
Columns in X 14
Columns in Z Per Subject 1
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 1557.41431080  
1 2 1382.60038946 0.00001092
2 1 1382.59792597 0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr > Z
UN(1,1) PersonID 0.6546 0.1088 6.01 <.0001
Residual   0.6079 0.04283 14.19 <.0001

Fit Statistics
-2 Log Likelihood 1382.6
AIC (smaller is better) 1414.6
AICC (smaller is better) 1415.7
BIC (smaller is better) 1457.1

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
1 174.82 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
1382.6 16 1414.6 1415.7 1431.8 1457.1 1473.1

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 2.9839 0.4722 142 6.32 <.0001 0.05 2.0505 3.9173
women -0.3511 0.2177 145 -1.61 0.1091 0.05 -0.7815 0.07928
age80 0.06816 0.03068 108 2.22 0.0284 0.05 0.007342 0.1290
women*age80 -0.09165 0.03434 108 -2.67 0.0088 0.05 -0.1597 -0.02358
PMmood2 1.8282 0.5104 142 3.58 0.0005 0.05 0.8193 2.8371
WPmood -0.00281 0.2713 429 -0.01 0.9917 0.05 -0.5361 0.5305
PMstressor40 0.8713 1.2129 132 0.72 0.4738 0.05 -1.5278 3.2705
stressor 0.2225 0.3984 411 0.56 0.5769 0.05 -0.5607 1.0057
women*PMstressor40 -1.4321 0.6733 127 -2.13 0.0354 0.05 -2.7644 -0.09970
women*stressor -0.1711 0.2066 404 -0.83 0.4081 0.05 -0.5773 0.2351
PMmood2*stressor 0.01152 0.4389 412 0.03 0.9791 0.05 -0.8512 0.8743
PMmood2*PMstressor40 -1.4700 1.2373 139 -1.19 0.2368 0.05 -3.9163 0.9764
WPmood*stressor 0.05900 0.4027 445 0.15 0.8836 0.05 -0.7325 0.8505
WPmood*PMstressor40 0.4427 0.5342 421 0.83 0.4077 0.05 -0.6074 1.4928

Type 3 Tests of Fixed Effects
Effect Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
women 1 145 2.60 2.60 0.1069 0.1091
age80 1 108 4.93 4.93 0.0263 0.0284
women*age80 1 108 7.12 7.12 0.0076 0.0088
PMmood2 1 142 12.83 12.83 0.0003 0.0005
WPmood 1 429 0.00 0.00 0.9917 0.9917
PMstressor40 1 132 0.52 0.52 0.4725 0.4738
stressor 1 411 0.31 0.31 0.5766 0.5769
women*PMstressor40 1 127 4.52 4.52 0.0334 0.0354
women*stressor 1 404 0.69 0.69 0.4076 0.4081
PMmood2*stressor 1 412 0.00 0.00 0.9791 0.9791
PMmood2*PMstressor40 1 139 1.41 1.41 0.2348 0.2368
WPmood*stressor 1 445 0.02 0.02 0.8835 0.8836
WPmood*PMstressor40 1 421 0.69 0.69 0.4073 0.4077

Estimates
Label Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept: Men 2.9839 0.4722 142 6.32 <.0001 0.05 2.0505 3.9173
Intercept: Women 2.6328 0.4509 141 5.84 <.0001 0.05 1.7413 3.5242
Intercept: Sex Diff -0.3511 0.2177 145 -1.61 0.1091 0.05 -0.7815 0.07928
Age Slope: Men 0.06816 0.03068 108 2.22 0.0284 0.05 0.007342 0.1290
Age Slope: Women -0.02349 0.01665 104 -1.41 0.1612 0.05 -0.05650 0.009520
Age Slope: Sex Diff -0.09165 0.03434 108 -2.67 0.0088 0.05 -0.1597 -0.02358
BP Negative Mood 1.8282 0.5104 142 3.58 0.0005 0.05 0.8193 2.8371
Contextual Negative Mood 1.8310 0.5451 180 3.36 0.0010 0.05 0.7554 2.9067
WP Negative Mood -0.00281 0.2713 429 -0.01 0.9917 0.05 -0.5361 0.5305
BP Stressors: Men 1.0938 1.1415 105 0.96 0.3402 0.05 -1.1697 3.3574
BP Stressors: Women -0.5094 0.9994 104 -0.51 0.6114 0.05 -2.4912 1.4725
BP Stressors: Sex Diff -1.6032 0.6402 105 -2.50 0.0138 0.05 -2.8727 -0.3336
Contextual Stressors: Men 0.8713 1.2129 132 0.72 0.4738 0.05 -1.5278 3.2705
Contextual Stressors: Women -0.5607 1.0738 137 -0.52 0.6024 0.05 -2.6841 1.5627
Contextual Stressors: Sex Diff -1.4321 0.6733 127 -2.13 0.0354 0.05 -2.7644 -0.09970
WP Stressors: Men 0.2225 0.3984 411 0.56 0.5769 0.05 -0.5607 1.0057
WP Stressors: Women 0.05139 0.3763 412 0.14 0.8914 0.05 -0.6882 0.7910
WP Stressors: Sex Diff -0.1711 0.2066 404 -0.83 0.4081 0.05 -0.5773 0.2351
Contextual Stressors per Day 0.1743 0.2426 132 0.72 0.4738 0.05 -0.3056 0.6541
BP Negative Mood by BP Stressors -1.4584 1.1479 104 -1.27 0.2067 0.05 -3.7346 0.8177
BP Negative Mood by Contextual Stressors -1.4700 1.2373 139 -1.19 0.2368 0.05 -3.9163 0.9764
BP Negative Mood by WP Stressors 0.01152 0.4389 412 0.03 0.9791 0.05 -0.8512 0.8743
Contextual Negative Mood by BP Stressors -1.9602 1.2227 134 -1.60 0.1113 0.05 -4.3786 0.4583
Contextual Negative Mood by Contextual Stressors -1.9127 1.3406 186 -1.43 0.1553 0.05 -4.5575 0.7321
Contextual Negative Mood by WP Stressors -0.04748 0.5410 425 -0.09 0.9301 0.05 -1.1109 1.0159
WP Negative Mood by BP Stressors 0.5017 0.4245 404 1.18 0.2380 0.05 -0.3328 1.3362
WP Negative Mood by Contextual Stressors 0.4427 0.5342 421 0.83 0.4077 0.05 -0.6074 1.4928
WP Negative Mood by WP Stressors 0.05900 0.4027 445 0.15 0.8836 0.05 -0.7325 0.8505

Contrasts
Label Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
Multivariate Test of 4 Negative Mood*Stressors Interactions 4 300 3.02 0.76 0.5542 0.5551


Likelihood Ratio Test for FitSex2 vs. FitMoodStressor4

Name Neg2LogLike Parms AIC BIC DevDiff DFdiff Pvalue
FitSex2 1385.6 12 1409.6 1441.5 . . .
FitMoodStressor4 1382.6 16 1414.6 1457.1 3.00901 4 0.55632


Total R2 (% Reduction) for PredSex2 vs. PredMoodStressor4

Name PredCorr TotalR2 TotalR2Diff
PredSex2 0.52917 0.28002 .
PredMoodStressor4 0.53440 0.28558 .005558062


Ch 8: Checking Inter-Variable Interactions via PMC Negative Mood by PMC Stressors

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
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 2
Columns in X 14
Columns in Z Per Subject 1
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 1557.41431080  
1 2 1382.60038946 0.00001092
2 1 1382.59792597 0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr > Z
UN(1,1) PersonID 0.6546 0.1088 6.01 <.0001
Residual   0.6079 0.04283 14.19 <.0001

Fit Statistics
-2 Log Likelihood 1382.6
AIC (smaller is better) 1414.6
AICC (smaller is better) 1415.7
BIC (smaller is better) 1457.1

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
1 174.82 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
1382.6 16 1414.6 1415.7 1431.8 1457.1 1473.1

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 3.0729 0.4388 107 7.00 <.0001 0.05 2.2030 3.9428
women -0.4195 0.2010 106 -2.09 0.0393 0.05 -0.8181 -0.02094
age80 0.06816 0.03068 108 2.22 0.0284 0.05 0.007342 0.1290
women*age80 -0.09165 0.03434 108 -2.67 0.0088 0.05 -0.1597 -0.02358
PMmood2 1.8328 0.4723 106 3.88 0.0002 0.05 0.8964 2.7693
WPmood 0.02079 0.1729 407 0.12 0.9044 0.05 -0.3191 0.3607
PMstressor40 1.0938 1.1415 105 0.96 0.3402 0.05 -1.1697 3.3574
WPstressor 0.2225 0.3984 411 0.56 0.5769 0.05 -0.5607 1.0057
women*PMstressor40 -1.6032 0.6402 105 -2.50 0.0138 0.05 -2.8727 -0.3336
women*WPstressor -0.1711 0.2066 404 -0.83 0.4081 0.05 -0.5773 0.2351
PMmood2*WPstressor 0.01152 0.4389 412 0.03 0.9791 0.05 -0.8512 0.8743
PMmood2*PMstressor40 -1.4584 1.1479 104 -1.27 0.2067 0.05 -3.7346 0.8177
WPmood*WPstressor 0.05900 0.4027 445 0.15 0.8836 0.05 -0.7325 0.8505
WPmood*PMstressor40 0.5017 0.4245 404 1.18 0.2380 0.05 -0.3328 1.3362

Type 3 Tests of Fixed Effects
Effect Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
women 1 106 4.35 4.35 0.0369 0.0393
age80 1 108 4.93 4.93 0.0263 0.0284
women*age80 1 108 7.12 7.12 0.0076 0.0088
PMmood2 1 106 15.06 15.06 0.0001 0.0002
WPmood 1 407 0.01 0.01 0.9043 0.9044
PMstressor40 1 105 0.92 0.92 0.3380 0.3402
WPstressor 1 411 0.31 0.31 0.5766 0.5769
women*PMstressor40 1 105 6.27 6.27 0.0123 0.0138
women*WPstressor 1 404 0.69 0.69 0.4076 0.4081
PMmood2*WPstressor 1 412 0.00 0.00 0.9791 0.9791
PMmood2*PMstressor40 1 104 1.61 1.61 0.2039 0.2067
WPmood*WPstressor 1 445 0.02 0.02 0.8835 0.8836
WPmood*PMstressor40 1 404 1.40 1.40 0.2373 0.2380

Estimates
Label Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
BP Negative Mood by BP Stressors -1.4584 1.1479 104 -1.27 0.2067 0.05 -3.7346 0.8177
BP Negative Mood by Contextual Stressors -1.4700 1.2373 139 -1.19 0.2368 0.05 -3.9163 0.9764
BP Negative Mood by WP Stressors 0.01152 0.4389 412 0.03 0.9791 0.05 -0.8512 0.8743
Contextual Negative Mood by BP Stressors -1.9602 1.2227 134 -1.60 0.1113 0.05 -4.3786 0.4583
Contextual Negative Mood by Contextual Stressors -1.9127 1.3406 186 -1.43 0.1553 0.05 -4.5575 0.7321
Contextual Negative Mood by WP Stressors -0.04748 0.5410 425 -0.09 0.9301 0.05 -1.1109 1.0159
WP Negative Mood by BP Stressors 0.5017 0.4245 404 1.18 0.2380 0.05 -0.3328 1.3362
WP Negative Mood by Contextual Stressors 0.4427 0.5342 421 0.83 0.4077 0.05 -0.6074 1.4928
WP Negative Mood by WP Stressors 0.05900 0.4027 445 0.15 0.8836 0.05 -0.7325 0.8505


Ch 8: Checking Inter-Variable Interactions via GMC Negative Mood by GMC Stressors

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
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 2
Columns in X 14
Columns in Z Per Subject 1
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 1557.41431080  
1 2 1382.60038946 0.00001092
2 1 1382.59792597 0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr > Z
UN(1,1) PersonID 0.6546 0.1088 6.01 <.0001
Residual   0.6079 0.04283 14.19 <.0001

Fit Statistics
-2 Log Likelihood 1382.6
AIC (smaller is better) 1414.6
AICC (smaller is better) 1415.7
BIC (smaller is better) 1457.1

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
1 174.82 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
1382.6 16 1414.6 1415.7 1431.8 1457.1 1473.1

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 2.9839 0.4722 142 6.32 <.0001 0.05 2.0505 3.9173
women -0.3511 0.2177 145 -1.61 0.1091 0.05 -0.7815 0.07928
age80 0.06816 0.03068 108 2.22 0.0284 0.05 0.007342 0.1290
women*age80 -0.09165 0.03434 108 -2.67 0.0088 0.05 -0.1597 -0.02358
PMmood2 1.8310 0.5451 180 3.36 0.0010 0.05 0.7554 2.9067
mood2 -0.00281 0.2713 429 -0.01 0.9917 0.05 -0.5361 0.5305
PMstressor40 0.8713 1.2129 132 0.72 0.4738 0.05 -1.5278 3.2705
stressor 0.2225 0.3984 411 0.56 0.5769 0.05 -0.5607 1.0057
women*PMstressor40 -1.4321 0.6733 127 -2.13 0.0354 0.05 -2.7644 -0.09970
women*stressor -0.1711 0.2066 404 -0.83 0.4081 0.05 -0.5773 0.2351
PMmood2*stressor -0.04748 0.5410 425 -0.09 0.9301 0.05 -1.1109 1.0159
PMmood2*PMstressor40 -1.9127 1.3406 186 -1.43 0.1553 0.05 -4.5575 0.7321
mood2*stressor 0.05900 0.4027 445 0.15 0.8836 0.05 -0.7325 0.8505
mood2*PMstressor40 0.4427 0.5342 421 0.83 0.4077 0.05 -0.6074 1.4928

Type 3 Tests of Fixed Effects
Effect Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
women 1 145 2.60 2.60 0.1069 0.1091
age80 1 108 4.93 4.93 0.0263 0.0284
women*age80 1 108 7.12 7.12 0.0076 0.0088
PMmood2 1 180 11.28 11.28 0.0008 0.0010
mood2 1 429 0.00 0.00 0.9917 0.9917
PMstressor40 1 132 0.52 0.52 0.4725 0.4738
stressor 1 411 0.31 0.31 0.5766 0.5769
women*PMstressor40 1 127 4.52 4.52 0.0334 0.0354
women*stressor 1 404 0.69 0.69 0.4076 0.4081
PMmood2*stressor 1 425 0.01 0.01 0.9301 0.9301
PMmood2*PMstressor40 1 186 2.04 2.04 0.1537 0.1553
mood2*stressor 1 445 0.02 0.02 0.8835 0.8836
mood2*PMstressor40 1 421 0.69 0.69 0.4073 0.4077

Estimates
Label Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
BP Negative Mood by BP Stressors -1.4584 1.1479 104 -1.27 0.2067 0.05 -3.7346 0.8177
BP Negative Mood by Contextual Stressors -1.4700 1.2373 139 -1.19 0.2368 0.05 -3.9163 0.9764
BP Negative Mood by WP Stressors 0.01152 0.4389 412 0.03 0.9791 0.05 -0.8512 0.8743
Contextual Negative Mood by BP Stressors -1.9602 1.2227 134 -1.60 0.1113 0.05 -4.3786 0.4583
Contextual Negative Mood by Contextual Stressors -1.9127 1.3406 186 -1.43 0.1553 0.05 -4.5575 0.7321
Contextual Negative Mood by WP Stressors -0.04748 0.5410 425 -0.09 0.9301 0.05 -1.1109 1.0159
WP Negative Mood by BP Stressors 0.5017 0.4245 404 1.18 0.2380 0.05 -0.3328 1.3362
WP Negative Mood by Contextual Stressors 0.4427 0.5342 421 0.83 0.4077 0.05 -0.6074 1.4928
WP Negative Mood by WP Stressors 0.05900 0.4027 445 0.15 0.8836 0.05 -0.7325 0.8505


Ch 8: Checking Inter-Variable Interactions via GMC Negative Mood by PMC Stressors

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
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 2
Columns in X 14
Columns in Z Per Subject 1
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 1557.41431080  
1 2 1382.60038946 0.00001092
2 1 1382.59792597 0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr > Z
UN(1,1) PersonID 0.6546 0.1088 6.01 <.0001
Residual   0.6079 0.04283 14.19 <.0001

Fit Statistics
-2 Log Likelihood 1382.6
AIC (smaller is better) 1414.6
AICC (smaller is better) 1415.7
BIC (smaller is better) 1457.1

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
1 174.82 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
1382.6 16 1414.6 1415.7 1431.8 1457.1 1473.1

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 3.0729 0.4388 107 7.00 <.0001 0.05 2.2030 3.9428
women -0.4195 0.2010 106 -2.09 0.0393 0.05 -0.8181 -0.02094
age80 0.06816 0.03068 108 2.22 0.0284 0.05 0.007342 0.1290
women*age80 -0.09165 0.03434 108 -2.67 0.0088 0.05 -0.1597 -0.02358
PMmood2 1.8120 0.4979 130 3.64 0.0004 0.05 0.8271 2.7970
mood2 0.02079 0.1729 407 0.12 0.9044 0.05 -0.3191 0.3607
PMstressor40 1.0938 1.1415 105 0.96 0.3402 0.05 -1.1697 3.3574
WPstressor 0.2225 0.3984 411 0.56 0.5769 0.05 -0.5607 1.0057
women*PMstressor40 -1.6032 0.6402 105 -2.50 0.0138 0.05 -2.8727 -0.3336
women*WPstressor -0.1711 0.2066 404 -0.83 0.4081 0.05 -0.5773 0.2351
PMmood2*WPstressor -0.04748 0.5410 425 -0.09 0.9301 0.05 -1.1109 1.0159
PMmood2*PMstressor40 -1.9602 1.2227 134 -1.60 0.1113 0.05 -4.3786 0.4583
mood2*WPstressor 0.05900 0.4027 445 0.15 0.8836 0.05 -0.7325 0.8505
mood2*PMstressor40 0.5017 0.4245 404 1.18 0.2380 0.05 -0.3328 1.3362

Type 3 Tests of Fixed Effects
Effect Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
women 1 106 4.35 4.35 0.0369 0.0393
age80 1 108 4.93 4.93 0.0263 0.0284
women*age80 1 108 7.12 7.12 0.0076 0.0088
PMmood2 1 130 13.25 13.25 0.0003 0.0004
mood2 1 407 0.01 0.01 0.9043 0.9044
PMstressor40 1 105 0.92 0.92 0.3380 0.3402
WPstressor 1 411 0.31 0.31 0.5766 0.5769
women*PMstressor40 1 105 6.27 6.27 0.0123 0.0138
women*WPstressor 1 404 0.69 0.69 0.4076 0.4081
PMmood2*WPstressor 1 425 0.01 0.01 0.9301 0.9301
PMmood2*PMstressor40 1 134 2.57 2.57 0.1089 0.1113
mood2*WPstressor 1 445 0.02 0.02 0.8835 0.8836
mood2*PMstressor40 1 404 1.40 1.40 0.2373 0.2380

Estimates
Label Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
BP Negative Mood by BP Stressors -1.4584 1.1479 104 -1.27 0.2067 0.05 -3.7346 0.8177
BP Negative Mood by Contextual Stressors -1.4700 1.2373 139 -1.19 0.2368 0.05 -3.9163 0.9764
BP Negative Mood by WP Stressors 0.01152 0.4389 412 0.03 0.9791 0.05 -0.8512 0.8743
Contextual Negative Mood by BP Stressors -1.9602 1.2227 134 -1.60 0.1113 0.05 -4.3786 0.4583
Contextual Negative Mood by Contextual Stressors -1.9127 1.3406 186 -1.43 0.1553 0.05 -4.5575 0.7321
Contextual Negative Mood by WP Stressors -0.04748 0.5410 425 -0.09 0.9301 0.05 -1.1109 1.0159
WP Negative Mood by BP Stressors 0.5017 0.4245 404 1.18 0.2380 0.05 -0.3328 1.3362
WP Negative Mood by Contextual Stressors 0.4427 0.5342 421 0.83 0.4077 0.05 -0.6074 1.4928
WP Negative Mood by WP Stressors 0.05900 0.4027 445 0.15 0.8836 0.05 -0.7325 0.8505


Eq 8.13: Adding 5 Intra-Variable Interactions to the Model for the Means
Using Person-Mean-Centering for Negative Mood, Grand-Mean-Centering for Stressors

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
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 2
Columns in X 15
Columns in Z Per Subject 1
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 1544.81269376  
1 2 1378.33696010 0.00000745
2 1 1378.33529770 0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr > Z
UN(1,1) PersonID 0.6218 0.1043 5.96 <.0001
Residual   0.6082 0.04285 14.19 <.0001

Fit Statistics
-2 Log Likelihood 1378.3
AIC (smaller is better) 1412.3
AICC (smaller is better) 1413.6
BIC (smaller is better) 1457.5

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
1 166.48 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
1378.3 17 1412.3 1413.6 1430.6 1457.5 1474.5

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 2.5680 0.3733 138 6.88 <.0001 0.05 1.8298 3.3062
women -0.3249 0.2161 145 -1.50 0.1349 0.05 -0.7521 0.1023
age80 0.07095 0.03007 109 2.36 0.0201 0.05 0.01134 0.1306
women*age80 -0.08966 0.03363 108 -2.67 0.0089 0.05 -0.1563 -0.02300
PMmood2 -0.2980 0.8016 111 -0.37 0.7108 0.05 -1.8865 1.2905
WPmood 0.3733 0.2595 426 1.44 0.1511 0.05 -0.1368 0.8834
PMstressor40 1.8898 0.6325 140 2.99 0.0033 0.05 0.6393 3.1403
stressor 0.1979 0.1752 404 1.13 0.2593 0.05 -0.1465 0.5423
women*PMstressor40 -1.3022 0.6618 128 -1.97 0.0513 0.05 -2.6118 0.007335
women*stressor -0.1738 0.2053 404 -0.85 0.3979 0.05 -0.5774 0.2299
PMmood2*PMmood2 -1.8365 0.7167 110 -2.56 0.0117 0.05 -3.2567 -0.4163
WPmood*WPmood -0.2657 0.3133 468 -0.85 0.3969 0.05 -0.8813 0.3500
PMmood2*WPmood 0.2767 0.3968 405 0.70 0.4860 0.05 -0.5033 1.0567
PMstressor40*PMstressor40 -0.3856 0.9842 176 -0.39 0.6957 0.05 -2.3279 1.5567
PMstressor40*stressor 0.1757 0.4861 404 0.36 0.7180 0.05 -0.7799 1.1313

Type 3 Tests of Fixed Effects
Effect Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
women 1 145 2.26 2.26 0.1328 0.1349
age80 1 109 5.57 5.57 0.0183 0.0201
women*age80 1 108 7.11 7.11 0.0077 0.0089
PMmood2 1 111 0.14 0.14 0.7101 0.7108
WPmood 1 426 2.07 2.07 0.1503 0.1511
PMstressor40 1 140 8.93 8.93 0.0028 0.0033
stressor 1 404 1.28 1.28 0.2586 0.2593
women*PMstressor40 1 128 3.87 3.87 0.0491 0.0513
women*stressor 1 404 0.72 0.72 0.3974 0.3979
PMmood2*PMmood2 1 110 6.57 6.57 0.0104 0.0117
WPmood*WPmood 1 468 0.72 0.72 0.3964 0.3969
PMmood2*WPmood 1 405 0.49 0.49 0.4856 0.4860
PMstressor40*PMstressor40 1 176 0.15 0.15 0.6952 0.6957
PMstressor40*stressor 1 404 0.13 0.13 0.7178 0.7180

Estimates
Label Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
BP Negative Mood: Linear -0.2980 0.8016 111 -0.37 0.7108 0.05 -1.8865 1.2905
BP Negative Mood: Quadratic -1.8365 0.7167 110 -2.56 0.0117 0.05 -3.2567 -0.4163
Contextual Negative Mood: Linear -0.6713 0.8487 138 -0.79 0.4303 0.05 -2.3494 1.0068
Contextual Negative Mood: Quadratic -2.3788 0.9306 264 -2.56 0.0111 0.05 -4.2112 -0.5465
WP Negative Mood: Linear 0.3733 0.2595 426 1.44 0.1511 0.05 -0.1368 0.8834
WP Negative Mood: Quadratic -0.2657 0.3133 468 -0.85 0.3969 0.05 -0.8813 0.3500
BP by WP Negative Mood 0.2767 0.3968 405 0.70 0.4860 0.05 -0.5033 1.0567
Contextual by WP Negative Mood 0.8081 0.7629 454 1.06 0.2901 0.05 -0.6912 2.3073
BP Stressor: Linear 2.0877 0.6196 129 3.37 0.0010 0.05 0.8619 3.3135
BP Stressor: Quadratic -0.2099 0.8569 104 -0.25 0.8069 0.05 -1.9092 1.4893
Contextual Stressors: Linear 1.8898 0.6325 140 2.99 0.0033 0.05 0.6393 3.1403
Contextual Stressors: Quadratic -0.3856 0.9842 176 -0.39 0.6957 0.05 -2.3279 1.5567
WP Stressors: Linear 0.1979 0.1752 404 1.13 0.2593 0.05 -0.1465 0.5423
BP/Contextual by WP Stressors 0.1757 0.4861 404 0.36 0.7180 0.05 -0.7799 1.1313
BP Negative Mood: Linear at 1 3.3749 0.8137 117 4.15 <.0001 0.05 1.7633 4.9865
BP Negative Mood: Linear at 3 -3.9710 2.1753 110 -1.83 0.0707 0.05 -8.2821 0.3402

Contrasts
Label Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
Multivariate Test of 5 Intra-Variable Interactions 5 253 7.44 1.49 0.1898 0.1940


Likelihood Ratio Test for FitSex2 vs. FitIntra5

Name Neg2LogLike Parms AIC BIC DevDiff DFdiff Pvalue
FitSex2 1385.6 12 1409.6 1441.5 . . .
FitIntra5 1378.3 17 1412.3 1457.5 7.27164 5 0.20121


Total R2 (% Reduction) for PredSex2 vs. PredIntra5

Name PredCorr TotalR2 TotalR2Diff
PredSex2 0.52917 0.28002 .
PredIntra5 0.55107 0.30368 0.023656


Eq 8.13reduced: Baseline Homogeneous Variance Model with Significant Fixed Effects Only
Using Person-Mean-Centering for Negative Mood, Grand-Mean-Centering for Stressors

The Mixed Procedure

Model Information
Data Set WORK.CHAPTER8
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 2
Columns in X 12
Columns in Z Per Subject 1
Subjects 105
Max Obs Per Subject 5

Number of Observations
Number of Observations Read 509
Number of Observations Used 509
Number of Observations Not Used 0

Iteration History
Iteration Evaluations -2 Log Like Criterion
0 1 1545.96902754  
1 2 1379.31123855 0.00000648
2 1 1379.30978989 0.00000000

Convergence criteria met.

Covariance Parameter Estimates
Cov Parm Subject Estimate Standard Error Z Value Pr > Z
UN(1,1) PersonID 0.6230 0.1045 5.96 <.0001
Residual   0.6094 0.04293 14.19 <.0001

Fit Statistics
-2 Log Likelihood 1379.3
AIC (smaller is better) 1407.3
AICC (smaller is better) 1408.2
BIC (smaller is better) 1444.5

Null Model Likelihood Ratio Test
DF Chi-Square Pr > ChiSq
1 166.66 <.0001

Information Criteria
Neg2LogLike Parms AIC AICC HQIC BIC CAIC
1379.3 14 1407.3 1408.2 1422.4 1444.5 1458.5

Solution for Fixed Effects
Effect Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept 2.4501 0.3473 117 7.05 <.0001 0.05 1.7623 3.1379
women -0.3300 0.2141 146 -1.54 0.1254 0.05 -0.7531 0.09316
age80 0.07222 0.02999 109 2.41 0.0177 0.05 0.01278 0.1317
women*age80 -0.09030 0.03364 108 -2.68 0.0084 0.05 -0.1570 -0.02362
PMmood2 -0.3358 0.7998 110 -0.42 0.6754 0.05 -1.9208 1.2492
WPmood 0.2631 0.2213 405 1.19 0.2351 0.05 -0.1719 0.6981
PMstressor40 1.9255 0.6005 124 3.21 0.0017 0.05 0.7370 3.1141
stressor 0.2205 0.1710 404 1.29 0.1981 0.05 -0.1158 0.5567
women*PMstressor40 -1.3214 0.6618 128 -2.00 0.0480 0.05 -2.6309 -0.01203
women*stressor -0.1824 0.2053 404 -0.89 0.3748 0.05 -0.5860 0.2212
PMmood2*PMmood2 -1.7753 0.7132 108 -2.49 0.0143 0.05 -3.1889 -0.3618
PMmood2*WPmood 0.2589 0.3962 405 0.65 0.5139 0.05 -0.5201 1.0378

Type 3 Tests of Fixed Effects
Effect Num DF Den DF Chi-Square F Value Pr > ChiSq Pr > F
women 1 146 2.38 2.38 0.1233 0.1254
age80 1 109 5.80 5.80 0.0160 0.0177
women*age80 1 108 7.21 7.21 0.0073 0.0084
PMmood2 1 110 0.18 0.18 0.6746 0.6754
WPmood 1 405 1.41 1.41 0.2344 0.2351
PMstressor40 1 124 10.28 10.28 0.0013 0.0017
stressor 1 404 1.66 1.66 0.1974 0.1981
women*PMstressor40 1 128 3.99 3.99 0.0458 0.0480
women*stressor 1 404 0.79 0.79 0.3743 0.3748
PMmood2*PMmood2 1 108 6.20 6.20 0.0128 0.0143
PMmood2*WPmood 1 405 0.43 0.43 0.5135 0.5139


Eq 8.13reduced: Baseline Homogeneous Variance Model with Significant Fixed Effects Only

The NLMIXED Procedure

Specifications
Data Set WORK.CHAPTER8
Dependent Variable symptoms
Distribution for Dependent Variable Normal
Random Effects U0i
Distribution for Random Effects Normal
Subject Variable PersonID
Optimization Technique Newton-Raphson
Integration Method Adaptive Gaussian Quadrature

Dimensions
Observations Used 509
Observations Not Used 0
Total Observations 509
Subjects 105
Max Obs Per Subject 5
Parameters 14
Quadrature Points 1

Parameters
fint fsex fage fsexage fbpmood fwpmood fcstress fwpstress f2sexstress f1sexstress fbpmood2 fbpwpmood varEint vU0int NegLogLike
2.45 -0.33 0.07 -0.09 -0.34 0.26 1.93 0.22 -1.33 -0.18 -1.78 0.26 -0.5 -0.47 689.667896

Iteration History
Iter   Calls NegLogLike Diff MaxGrad Slope
1   32 689.654896 0.013 0.019887 -0.02603
2   48 689.654895 1.037E-6 3.982E-6 -2.07E-6

NOTE: ABSGCONV convergence criterion satisfied.

Fit Statistics
-2 Log Likelihood 1379.3
AIC (smaller is better) 1407.3
AICC (smaller is better) 1408.2
BIC (smaller is better) 1444.5

Parameter Estimates
Parameter Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Gradient
fint 2.4501 0.3473 104 7.05 <.0001 0.05 1.7613 3.1389 -1.29E-8
fsex -0.3300 0.2141 104 -1.54 0.1263 0.05 -0.7546 0.09462 1.39E-8
fage 0.07222 0.03000 104 2.41 0.0178 0.05 0.01274 0.1317 3.982E-6
fsexage -0.09030 0.03364 104 -2.68 0.0085 0.05 -0.1570 -0.02359 2.989E-6
fbpmood -0.3358 0.7998 104 -0.42 0.6754 0.05 -1.9219 1.2502 5.512E-8
fwpmood 0.2631 0.2213 104 1.19 0.2371 0.05 -0.1757 0.7019 -1.09E-8
fcstress 1.9255 0.6005 104 3.21 0.0018 0.05 0.7347 3.1164 2.38E-9
fwpstress 0.2205 0.1710 104 1.29 0.2003 0.05 -0.1187 0.5597 2.376E-9
f2sexstress -1.3214 0.6618 104 -2.00 0.0485 0.05 -2.6338 -0.00914 7.847E-9
f1sexstress -0.1824 0.2053 104 -0.89 0.3763 0.05 -0.5895 0.2247 2.145E-8
fbpmood2 -1.7753 0.7132 104 -2.49 0.0144 0.05 -3.1896 -0.3611 -3.66E-8
fbpwpmood 0.2589 0.3962 104 0.65 0.5150 0.05 -0.5269 1.0447 7.66E-9
varEint -0.4954 0.07045 104 -7.03 <.0001 0.05 -0.6351 -0.3557 -4.81E-7
vU0int -0.4731 0.1677 104 -2.82 0.0057 0.05 -0.8055 -0.1406 -3.83E-7

Additional Estimates
Label Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Level-1 Residual Variance 0.6093 0.04293 104 14.19 <.0001 0.05 0.5242 0.6945
Level-2 Random Intercept Variance 0.6231 0.1045 104 5.96 <.0001 0.05 0.4159 0.8302


Eq 8.14: Add Random Intercept Variance Heterogeneity by Sex, Age, L2 Negative Mood, and L2 Stressors

The NLMIXED Procedure

Specifications
Data Set WORK.CHAPTER8
Dependent Variable symptoms
Distribution for Dependent Variable Normal
Random Effects U0i
Distribution for Random Effects Normal
Subject Variable PersonID
Optimization Technique Newton-Raphson
Integration Method Adaptive Gaussian Quadrature

Dimensions
Observations Used 509
Observations Not Used 0
Total Observations 509
Subjects 105
Max Obs Per Subject 5
Parameters 18
Quadrature Points 1

Parameters
fint fsex fage fsexage fbpmood fwpmood fcstress fwpstress f2sexstress f1sexstress fbpmood2 fbpwpmood varEint vU0int vU0sex vU0age vU0bpmood vU0bpstress NegLogLike
2.45 -0.33 0.07 -0.09 -0.34 0.26 1.93 0.22 -1.33 -0.18 -1.78 0.26 -0.5 -0.47 0 0 0 0 689.667896

Iteration History
Iter   Calls NegLogLike Diff MaxGrad Slope
1   40 685.631025 4.03687 14.53166 -8.36325
2   60 685.566275 0.064751 0.484818 -0.12684
3   80 685.566191 0.000084 0.000994 -0.00017
4   100 685.566191 2.92E-10 3.917E-9 -584E-12

NOTE: GCONV convergence criterion satisfied.

Fit Statistics
-2 Log Likelihood 1371.1
AIC (smaller is better) 1407.1
AICC (smaller is better) 1408.5
BIC (smaller is better) 1454.9

Parameter Estimates
Parameter Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Gradient
fint 2.4232 0.3430 104 7.06 <.0001 0.05 1.7430 3.1033 -439E-12
fsex -0.3380 0.2103 104 -1.61 0.1110 0.05 -0.7550 0.07899 -476E-12
fage 0.07627 0.03062 104 2.49 0.0143 0.05 0.01554 0.1370 3.917E-9
fsexage -0.08751 0.03409 104 -2.57 0.0117 0.05 -0.1551 -0.01991 3.541E-9
fbpmood -0.2133 0.7833 104 -0.27 0.7859 0.05 -1.7667 1.3401 4.63E-10
fwpmood 0.2613 0.2212 104 1.18 0.2401 0.05 -0.1773 0.7000 1.99E-12
fcstress 1.8842 0.6088 104 3.10 0.0025 0.05 0.6770 3.0914 1.1E-10
fwpstress 0.2246 0.1710 104 1.31 0.1919 0.05 -0.1145 0.5636 -103E-12
f2sexstress -1.2272 0.6700 104 -1.83 0.0699 0.05 -2.5559 0.1014 1.02E-10
f1sexstress -0.1863 0.2052 104 -0.91 0.3659 0.05 -0.5932 0.2205 -101E-12
fbpmood2 -1.5868 0.6769 104 -2.34 0.0210 0.05 -2.9291 -0.2445 -344E-12
fbpwpmood 0.2561 0.3960 104 0.65 0.5192 0.05 -0.5292 1.0415 1.9E-13
varEint -0.4967 0.07034 104 -7.06 <.0001 0.05 -0.6362 -0.3572 -126E-12
vU0int -1.1026 0.7899 104 -1.40 0.1658 0.05 -2.6690 0.4639 -21E-11
vU0sex -0.1775 0.3852 104 -0.46 0.6459 0.05 -0.9413 0.5863 -207E-12
vU0age 0.03861 0.03293 104 1.17 0.2437 0.05 -0.02669 0.1039 6.49E-10
vU0bpmood -0.7100 0.8477 104 -0.84 0.4042 0.05 -2.3911 0.9711 1.67E-10
vU0bpstress 1.5812 0.6028 104 2.62 0.0100 0.05 0.3858 2.7766 2.82E-11

Contrasts
Label Num DF Den DF F Value Pr > F
Multivariate Test of 4 Predictors of Random Intercept Variance Heterogeneity 4 104 1.92 0.1130

Additional Estimates
Label Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Level-1 Residual Variance 0.6086 0.04281 104 14.22 <.0001 0.05 0.5237 0.6935
Level-2 Random Intercept Variance 0.3320 0.2623 104 1.27 0.2084 0.05 -0.1881 0.8521


Eq 8.15: Add Residual Variance Heterogeneity by Sex, Age, Both Negative Mood, and Both Stressors

The NLMIXED Procedure

Specifications
Data Set WORK.CHAPTER8
Dependent Variable symptoms
Distribution for Dependent Variable Normal
Random Effects U0i
Distribution for Random Effects Normal
Subject Variable PersonID
Optimization Technique Newton-Raphson
Integration Method Adaptive Gaussian Quadrature

Dimensions
Observations Used 509
Observations Not Used 0
Total Observations 509
Subjects 105
Max Obs Per Subject 5
Parameters 24
Quadrature Points 1

Parameters
fint fsex fage fsexage fbpmood fwpmood fcstress fwpstress f2sexstress f1sexstress fbpmood2 fbpwpmood varEint varEsex varEage varEbpmood varEbpstress varEwpmood varEwpstress vU0int vU0sex vU0age vU0bpmood vU0bpstress NegLogLike
2.45 -0.33 0.07 -0.09 -0.34 0.26 1.93 0.22 -1.33 -0.18 -1.78 0.26 -0.5 0 0 0 0 0 0 -0.47 0 0 0 0 689.667896

Iteration History
Iter   Calls NegLogLike Diff MaxGrad Slope
1   52 673.905929 15.76197 19.17296 -33.0308
2   78 673.172251 0.733677 1.713376 -1.41624
3   104 673.169487 0.002764 0.012275 -0.00551
4   130 673.169487 1.099E-7 7.751E-7 -2.2E-7

NOTE: ABSGCONV convergence criterion satisfied.

Fit Statistics
-2 Log Likelihood 1346.3
AIC (smaller is better) 1394.3
AICC (smaller is better) 1396.8
BIC (smaller is better) 1458.0

Parameter Estimates
Parameter Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Gradient
fint 2.4342 0.3656 104 6.66 <.0001 0.05 1.7093 3.1592 -1.44E-7
fsex -0.3371 0.2083 104 -1.62 0.1086 0.05 -0.7501 0.07590 -1.39E-7
fage 0.07410 0.03061 104 2.42 0.0172 0.05 0.01340 0.1348 7.751E-7
fsexage -0.08544 0.03419 104 -2.50 0.0140 0.05 -0.1532 -0.01764 7.006E-7
fbpmood -0.1565 0.8907 104 -0.18 0.8608 0.05 -1.9229 1.6098 1.179E-7
fwpmood 0.1523 0.3170 104 0.48 0.6319 0.05 -0.4763 0.7809 2.439E-8
fcstress 1.9172 0.5957 104 3.22 0.0017 0.05 0.7359 3.0986 2.696E-8
fwpstress 0.2096 0.1610 104 1.30 0.1959 0.05 -0.1097 0.5289 -2.83E-8
f2sexstress -1.2466 0.6592 104 -1.89 0.0614 0.05 -2.5538 0.06055 2.649E-8
f1sexstress -0.1763 0.1951 104 -0.90 0.3681 0.05 -0.5632 0.2105 -2.64E-8
fbpmood2 -1.5360 0.7473 104 -2.06 0.0423 0.05 -3.0178 -0.05409 -1.03E-7
fbpwpmood 0.08260 0.5216 104 0.16 0.8745 0.05 -0.9518 1.1170 -2.04E-9
varEint -0.08380 0.3079 104 -0.27 0.7860 0.05 -0.6943 0.5267 -6.2E-8
varEsex 0.07056 0.1664 104 0.42 0.6723 0.05 -0.2593 0.4004 -4.71E-8
varEage -0.00322 0.01310 104 -0.25 0.8065 0.05 -0.02919 0.02276 -5.13E-8
varEbpmood 0.6965 0.3369 104 2.07 0.0412 0.05 0.02840 1.3647 2.497E-8
varEbpstress 0.6980 0.3153 104 2.21 0.0290 0.05 0.07277 1.3232 -4.97E-9
varEwpmood 0.02616 0.3095 104 0.08 0.9328 0.05 -0.5876 0.6400 6.266E-9
varEwpstress -0.00901 0.2178 104 -0.04 0.9671 0.05 -0.4409 0.4229 -2.97E-8
vU0int -1.0810 0.8060 104 -1.34 0.1828 0.05 -2.6794 0.5174 -3.4E-8
vU0sex -0.1526 0.3840 104 -0.40 0.6919 0.05 -0.9140 0.6088 -3.29E-8
vU0age 0.03917 0.03203 104 1.22 0.2241 0.05 -0.02435 0.1027 1.973E-7
vU0bpmood -0.6983 0.8723 104 -0.80 0.4252 0.05 -2.4282 1.0315 2.785E-8
vU0bpstress 1.4248 0.5869 104 2.43 0.0169 0.05 0.2609 2.5887 6.365E-9

Contrasts
Label Num DF Den DF F Value Pr > F
Multivariate Test of 6 Predictors of Residual Variance Heterogeneity 6 104 3.95 0.0014

Additional Estimates
Label Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Level-1 Residual Variance 0.9196 0.2831 104 3.25 0.0016 0.05 0.3581 1.4811
Level-2 Random Intercept Variance 0.3393 0.2734 104 1.24 0.2175 0.05 -0.2030 0.8815


Ch 8: Final Heterogeneous Variance Model

The NLMIXED Procedure

Specifications
Data Set WORK.CHAPTER8
Dependent Variable symptoms
Distribution for Dependent Variable Normal
Random Effects U0i
Distribution for Random Effects Normal
Subject Variable PersonID
Optimization Technique Newton-Raphson
Integration Method Adaptive Gaussian Quadrature

Dimensions
Observations Used 509
Observations Not Used 0
Total Observations 509
Subjects 105
Max Obs Per Subject 5
Parameters 15
Quadrature Points 1

Parameters
fint fsex fage fsexage fbpmood fwpmood fcstress fwpstress f2sexstress f1sexstress varEint varEbpmood varEbpstress vU0int vU0bpstress NegLogLike
2.45 -0.33 0.07 -0.09 1.66 0.26 1.93 0.22 -1.33 -0.18 -0.5 0 0 -0.47 0 701.694823

Iteration History
Iter   Calls NegLogLike Diff MaxGrad Slope
1   34 687.486737 14.20809 46.3476 -55.4491
2   51 676.789293 10.69744 7.699735 -18.9899
3   68 675.92789 0.861403 1.32277 -1.63614
4   85 675.917527 0.010363 0.014223 -0.02054
5   102 675.917525 2.611E-6 5.271E-6 -5.22E-6

NOTE: ABSGCONV convergence criterion satisfied.

Fit Statistics
-2 Log Likelihood 1351.8
AIC (smaller is better) 1381.8
AICC (smaller is better) 1382.8
BIC (smaller is better) 1421.6

Parameter Estimates
Parameter Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Gradient
fint 2.8033 0.3679 104 7.62 <.0001 0.05 2.0737 3.5329 5.271E-6
fsex -0.3432 0.2060 104 -1.67 0.0988 0.05 -0.7517 0.06534 4.208E-6
fage 0.06782 0.02980 104 2.28 0.0249 0.05 0.008729 0.1269 -1.44E-6
fsexage -0.08734 0.03303 104 -2.64 0.0095 0.05 -0.1528 -0.02184 4.216E-7
fbpmood 1.6584 0.3974 104 4.17 <.0001 0.05 0.8704 2.4464 -4.67E-6
fwpmood 0.1022 0.1473 104 0.69 0.4892 0.05 -0.1899 0.3944 -2.84E-9
fcstress 2.0445 0.6011 104 3.40 0.0010 0.05 0.8526 3.2365 -1.56E-6
fwpstress 0.2057 0.1647 104 1.25 0.2145 0.05 -0.1209 0.5323 5.378E-7
f2sexstress -1.3649 0.6707 104 -2.04 0.0444 0.05 -2.6950 -0.03488 -1.3E-6
f1sexstress -0.1768 0.1980 104 -0.89 0.3739 0.05 -0.5694 0.2158 3.796E-7
varEint -0.01069 0.2766 104 -0.04 0.9693 0.05 -0.5593 0.5379 -1.01E-6
varEbpmood 0.7229 0.3287 104 2.20 0.0301 0.05 0.07104 1.3748 8.636E-7
varEbpstress 0.6773 0.2250 104 3.01 0.0033 0.05 0.2311 1.1236 2.647E-7
vU0int -0.5725 0.1712 104 -3.34 0.0011 0.05 -0.9120 -0.2331 -1.23E-6
vU0bpstress 1.3877 0.5348 104 2.59 0.0108 0.05 0.3272 2.4483 3.085E-7

Additional Estimates
Label Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper
Intercept: Men 2.8033 0.3679 104 7.62 <.0001 0.05 2.0737 3.5329
Intercept: Women 2.4601 0.3416 104 7.20 <.0001 0.05 1.7827 3.1375
Intercept: Sex Diff -0.3432 0.2060 104 -1.67 0.0988 0.05 -0.7517 0.06534
Age Slope: Men 0.06782 0.02980 104 2.28 0.0249 0.05 0.008729 0.1269
Age Slope: Women -0.01952 0.01505 104 -1.30 0.1976 0.05 -0.04937 0.01033
Age Slope: Sex Diff -0.08734 0.03303 104 -2.64 0.0095 0.05 -0.1528 -0.02184
BP Negative Mood 1.6584 0.3974 104 4.17 <.0001 0.05 0.8704 2.4464
Contextual Negative Mood 1.5562 0.4239 104 3.67 0.0004 0.05 0.7155 2.3968
WP Negative Mood 0.1022 0.1473 104 0.69 0.4892 0.05 -0.1899 0.3944
BP Stress: Men 2.2502 0.5774 104 3.90 0.0002 0.05 1.1053 3.3951
BP Stress: Women 0.7085 0.3137 104 2.26 0.0260 0.05 0.08652 1.3305
BP Stress: Sex Diff -1.5417 0.6402 104 -2.41 0.0178 0.05 -2.8114 -0.2721
Contextual Stressors: Men 2.0445 0.6011 104 3.40 0.0010 0.05 0.8526 3.2365
Contextual Stressors: Women 0.6796 0.3329 104 2.04 0.0437 0.05 0.01942 1.3398
Contextual Stressors: Sex Diff -1.3649 0.6707 104 -2.04 0.0444 0.05 -2.6950 -0.03488
WP Stressors: Men 0.2057 0.1647 104 1.25 0.2145 0.05 -0.1209 0.5323
WP Stressors: Women 0.02888 0.1122 104 0.26 0.7974 0.05 -0.1936 0.2514
WP Stressors: Sex Diff -0.1768 0.1980 104 -0.89 0.3739 0.05 -0.5694 0.2158
Contextual Stressors per Day: Men 0.4089 0.1202 104 3.40 0.0010 0.05 0.1705 0.6473
Contextual Stressors per Day: Women 0.1359 0.06658 104 2.04 0.0437 0.05 0.003883 0.2680
Men, PMstressor=20%, Stressor=0 2.3944 0.3920 104 6.11 <.0001 0.05 1.6171 3.1717
Men, PMstressor=20%, Stressor=1 2.6001 0.4121 104 6.31 <.0001 0.05 1.7829 3.4173
Men, PMstressor=80%, Stressor=0 3.6211 0.4307 104 8.41 <.0001 0.05 2.7669 4.4753
Men, PMstressor=80%, Stressor=1 3.8268 0.4107 104 9.32 <.0001 0.05 3.0124 4.6412
Women, PMstressor=20%, Stressor=0 2.3242 0.3585 104 6.48 <.0001 0.05 1.6133 3.0351
Women, PMstressor=20%, Stressor=1 2.3531 0.3680 104 6.39 <.0001 0.05 1.6234 3.0828
Women, PMstressor=80%, Stressor=0 2.7320 0.3459 104 7.90 <.0001 0.05 2.0460 3.4180
Women, PMstressor=80%, Stressor=1 2.7609 0.3340 104 8.27 <.0001 0.05 2.0986 3.4231


Ch 8: Final Heterogeneous Variance Model

The CORR Procedure

2 Variables: symptoms Pred

Simple Statistics
Variable N Mean Std Dev Sum Minimum Maximum Label
symptoms 509 1.27308 1.32439 648.00000 0 5.00000 symptoms: # Daily Physical Symptoms (0=5)
Pred 509 1.28561 0.74722 654.37298 -0.18243 4.54449 Predicted Value

Pearson Correlation Coefficients, N = 509
Prob > |r| under H0: Rho=0
  symptoms Pred
symptoms
symptoms: # Daily Physical Symptoms (0=5)
1.00000
 
0.52896
<.0001
Pred
Predicted Value
0.52896
<.0001
1.00000