Table of Contents
Section I: Building Blocks for Longitudinal Analysis
CHAPTER 1: Introduction to the Analysis of Longitudinal Data
CHAPTER 2: Between-Person Analysis and Interpretation of Interactions
CHAPTER 3: Introduction to Within-Person Analysis and Model Comparisons
Section II: Modeling the Effects of Time
CHAPTER 4: Describing Within-Person Fluctuation over Time
CHAPTER 5: Introduction to Random Effects of Time and Model Estimation
CHAPTER 6: Describing Within-Person Change over Time
Section III: Modeling the Effects of Predictors
CHAPTER 7: Time-Invariant Predictors in Longitudinal Models
CHAPTER 8: Time-Varying Predictors in Models of Within-Person Fluctuation
CHAPTER 9: Time-Varying Predictors in Models of Within-Person Change
Section IV: Advanced Applications
CHAPTER 10: Analysis over Alternative Metrics and Multiple Levels of Time
CHAPTER 11: Analysis of Individuals within Groups over Time
CHAPTER 12: Analysis of Repeated Measures Designs Not Involving Time
CHAPTER 13: Additional Considerations and Future Directions

Note: SAS was used for all reported analyses; results from other programs may differ slightly (especially when using ML or Bayes instead of REML).
Did you find an error or have a suggestion? Please email me. Current erata are at the bottom of the page.
Some of the book's examples are also available using R as created by others; please see this link to them via Github.

Example Materials by Chapter Below: For all models that could be estimated within each program for each chapter example,
View shows a new simultaneous window of syntax and ouptut, and
Save provides a .zip folder of the program data, syntax, and output.
SAS
MIXED 		SPSS
MIXED 		STATA
MIXED 		MPLUS
(using ML)		 Excel Spreadsheets
for Additional Calculations*
General Notes about Program Syntax and Models by Chapter View View View View
Chapter 2: Interaction Terms in General Linear Models View  or  Save View  or  Save View  or  Save View  or  Save Save
Chapter 3a: Between-Person and Within-Person Variance Models for Two-Occasion Data View  or  Save View  or  Save View  or  Save View  or  Save (n/a)
Chapter 3b: Analysis of Variance Models for Six-Occasion Data View  or  Save View  or  Save View  or  Save View  or  Save Save
Chapter 4: Alternative Covariance Structure Models for Within-Person Fluctuation View  or  Save View  or  Save View  or  Save View  or  Save Save
Chapter 5: Random Effects of Time View  or  Save View  or  Save View  or  Save View  or  Save Save
Chapter 6: Random Effects Models for Nonlinear Change over Time View  or  Save View  or  Save View  or  Save View  or  Save Save
Chapter 7a: Time-Invariant Predictors in Models of Fluctuation View  or  Save View  or  Save View  or  Save View  or  Save Save
Chapter 7b: Time-Invariant Predictors in Models of Change View  or  Save View  or  Save View  or  Save View  or  Save Save
Chapter 8: Time-Varying Predictors in Models of Fluctuation View  or  Save View  or  Save View  or  Save View  or  Save Save
Chapter 9: Time-Varying Predictors in Models of Change View  or  Save View  or  Save View  or  Save View  or  Save Save
Chapter 10a: Two-Level Models of Alternative Metrics of Time View  or  Save View  or  Save View  or  Save View  or  Save Save
Chapter 10b: Three-Level Models of Separable Dimensions of Time View  or  Save View  or  Save View  or  Save View  or  Save Save
Chapter 11a: Three-Level Models of Persons Nested in Time-Invariant Groups View  or  Save View  or  Save View  or  Save View  or  Save Save
Chapter 11b: Two-Level Models of Persons Crossed with Time-Varying Groups View  or  Save View  or  Save View  or  Save currently not available in ML Save
Chapter 12: Two-Level Crossed Models for Other Repeated Measures Data View  or  Save View  or  Save View  or  Save currently not available in ML Save
Chapter 13: Power Analysis

Cohen Single-Level Power Tables		 (n/a) (n/a) (n/a) (n/a) Table 13.1 and Figure 13.1


* Additional spreadsheet calculations include where relevant for each chapter: Likelikhood Ratio Tests (LRTs), Random Effects
  Confidence Intervals (CIs), Pseudo-R2 (R2), Regions of Significance (Regions), and Figures of Predicted Values (Figures).

Thank you to Ryan Hoffman for his custom java script that uses html to provide color-coding of the program syntax.

Errata (last updated 8/5/21):

p. 103: The default estimator in STATA MIXED (and the older XTMIXED) is ML, not REML as stated.

p. 185: In Equation 5.14, the GLM matrix solution should end in X'Y, not X'X.

p. 185: In Equation 5.19, the matrix R should be replaced by the scalar σ2 for the residual variance.

p. 367: The composite equation should replace the current γ24 with the γ30 term from the level-2 model above.

p. 371: The composite equation is missing the γ40 term from the level-2 model above.

p. 420: In the the equation at the top of Figure 9.5, all betas should have an i in the second subscript instead of a 0.

p. 421: β3i should be β3iR

p. 424: The formula for eti should have β1i instead of β0i in front of (Ageti − 18)

p. 507: The subscript on tau-squared in row 2, column 2 of the G matrix should be 10, not 01.

p. 538: The subscript on the predictor for γ300 should be Aggtsc instead of Aggsc.