This book will show how to estimate and interpret fixed-effects models in a variety of different modeling contexts: linear models, logistic models, Poisson models, Cox regression models, and structural equation models. Both advantages and disadvantages of fixed-effects models will be considered, along with detailed comparisons with random-effects models. Written at a level appropriate for anyone who has taken a year of statistics, the book will be appropriate as a supplement for graduate courses in regression or linear regression as well as an aid to researchers who have repeated measures or cross-sectional data.

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Articles li�s � Fixed Effects Regression Models: 160 (Quantitative...

Fixed Effects Regression Models: 160 (Quantitative Applications in the Social Sciences)

Paul D. Allison

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