Longitudinal and Panel Data: Analysis and Applications in the Social Sciences

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Overview

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.
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Product Details

  • ISBN-13: 9780521535380
  • Publisher: Cambridge University Press
  • Publication date: 8/28/2004
  • Edition description: New Edition
  • Pages: 467
  • Product dimensions: 5.98 (w) x 8.98 (h) x 1.06 (d)

Meet the Author

E. W. Frees is a Professor of Business at the University of Wisconsin-Madison and is holder of the Fortis Health Insurance Professorship of Actuarial Science. He is a Fellow of both the Society of Actuaries and the American Statistical Association. He has served in several editorial capacities including Editor of the North American Actuarial Journal and Associate Editor for Insurance: Mathematics and Economics. An award-winning researcher, he as published in the leading refereed academic journals in Business and Economics and Theoretical and Applied Statistics.
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Table of Contents

1 Introduction 1
2 Fixed-effects models 18
3 Models with random effects 72
4 Prediction and Bayesian inference 125
5 Multilevel models 166
6 Stochastic regressors 199
7 Modeling issues 242
8 Dynamic models 277
9 Binary dependent variables 312
10 Generalized linear models 350
11 Categorical dependent variables and survival models 387
App. A Elements of matrix algebra 417
App. B Normal distribution 422
App. C Likelihood-based inference 424
App. D State space model and the Kalman filter 434
App. E Symbols and notation 439
App. F Selected longitudinal and panel data sets 445
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