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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.
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.