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.
Jeffrey D. Long, PhD, is Professor of Psychiatry in the Carver College of Medicine at the University of Iowa. He is also the Head Statistician for Neurobiological Predictors of Huntington's Disease (PREDICT-HD), a longitudinal NIH-funded study of early detection of Huntington's Disease. His undergraduate degree is from the University of California at Los Angeles, and his doctoral degree is from the University of Southern California in the area of quantitative psychology.
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