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. 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.
For many years, the most challenging project in statistics has been the effort to devise methods for making valid causal inferences from nonexperimental data. And within that project, the most difficult problem is how to statistically control for variables that cannot be observed. For ...