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Longitudinal Data Analysis for the Behavioral Sciences Using R
- Jeffrey D. Long - University of Iowa, USA
December 2011 | 568 pages | SAGE Publications, Inc
This book is a practical guide for the analysis of longitudinal behavioural data. Longitudinal data consist of repeated measures collected on the same subjects over time. Such data is collected by researchers in psychology, education, organization studies, public policy, and related fields. A variety of substantive research questions are addressed with longitudinal data, including how student achievement changes over time, how psychopathology develops, and how intra-group conflict evolves.
About 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
I am currently trying to introduce this text to my course this spring, though I am getting some resistance. I'm finding that most of my students are not familiar enough with R and I can't devote enough class time to help them learn R AND learn about growth modeling. At least for now, considering how the course is structured, I plan to use it as a supplemental text.
Educational Psychology, University of Illinois - Chicago
March 5, 2012
