Description
Book SynopsisThis book is unique in its focus on showing students in the behavioral sciences how to analyze longitudinal data using R software. The book focuses on application, making it practical and accessible to students in psychology, education, and related fields, who have a basic foundation in statistics. It provides explicit instructions in R computer programming throughout the book, showing students exactly how a specific analysis is carried out and how output is interpreted.
This text excels in the explanation of models with the side-by-side use of R, so the audience can see the models in action. There is a gentle coverage of the mathematics driving the models, which does not seem intimidating to a non technical audience.William Anderson, Cornell University
Table of ContentsAbout the Author Preface Chapter 1. Introduction Chapter 2. Brief Introduction to R Chapter 3. Data Structures and Longitudinal Analysis Chapter 4. Graphing Longitudinal Data Chapter 5. Introduction to Linear Mixed Effects Regression Chapter 6. Overview of Maximum Likelihood Estimation Chapter 7. Multimodel Inference and Akaike′s Information Criterion Chapter 8. Likelihood Ratio Test Chapter 9. Selecting Time Predictors Chapter 10. Selecting Random Effects Chapter 11. Extending Linear Mixed Effects Regression Chapter 12. Modeling Nonlinear Change Chapter 13. Advanced Topics Appendix: Soft Introduction to Matrix Algebra References Author Index Subject Index
