Longitudinal and Panel Data: Analysis and Applications in the Social Sciences (Paperback)
Edward W. Frees (Author)

Editorial Reviews

Product Description
Focusing on an analysis of models and data that arise from repeated observations of a cross-section of individuals, households or firms, this book also covers important applications within business, economics, education, political science and other social science disciplines. The author introduces the foundations of longitudinal and panel data analysis at a level suitable for quantitatively oriented social science graduate students as well as individual researchers. He emphasizes mathematical and statistical fundamentals but also demonstrates substantive applications from across the social sciences. These applications are enhanced by real-world data sets and software programs in SAS and Stata.

Book Description
Focusing on an analysis of models and data that arise from repeated observations of a cross-section of individuals, households or firms, this book also covers important applications within business, economics, education, political science and other social science disciplines. The author introduces the foundations of longitudinal and panel data analysis at a level suitable for quantitatively oriented graduate social science students as well as individual researchers. He emphasizes mathematical and statistical fundamentals but also demonstrates substantive applications from across the social sciences. These applications are enhanced by real-world data sets and software programs in SAS and Stata.

Product Details Paperback: 484 pages Publisher: Cambridge University Press (August 16, 2004) Language: English ISBN-10: 0521535387 ISBN-13: 978-0521535380

Contents

1. Introduction;

Part I. Linear Models:
2. Fixed effects models;
3. Models with random effects;
4. Prediction and Bayesian Inference;
5. Multilevel models;
6. Random regressors;
7. Modeling issues;
8. Dynamic models;

Part II. Nonlinear Models:
9. Binary dependent variables;
10. Generalized linear models;
11. Categorical dependent variables and survival models;

Appendix A. Elements of Matrix Algebra;
Appendix B. Normal distribution;
Appendix C. Likelihood-based inference;
Appendix D. Kalman Filter;
Appendix E. Symbols and notation;
Appendix F. Selected longitudinal and panel data sets;
Appendix G. References.