The book provides a simple, intuitive introduction to regression models for qualitative and discrete dependent variables, to sample selection models, and to event history models, all in the context of maximum likelihood estimation. It presents a wide range of commonly used models. The book...

Machine generated contents note: 1 Classical Statistical Procedures -- 1.1 Introduction -- 1.2 The Score Vector, the Information Matrix, and the Cramer-Rao -- Lower Bound -- 1.3 Maximum Likelihood Estimators and Test Procedures -- 1.4 Nuisance Parameters -- 1.5 Differentiation and Asymptotics --...