Regression Models for Categorical Dependent Variables Using Stata

Nearly 50 Per cent longer than the previous edition, the book covers new topics for fitting and interpretating models included in Stata 9, such as multinomial probit models, the stereotype logistic model, and zero-truncated count models. Many of the interpretation techniques have been updated to include interval as well as point estimates. New to the Second Edition: Regression models, including the zero-truncated Poisson and the zero-truncated negative binomial models, the hurdle model for counts, the stereotype logistic regression model, the rank-ordered logit model, and the multinomial probit model Stata commands, such as estat, which provides a uniform way to access statistics useful for postestimation interpretation. Expanded suite of programs known as SPost Inclusion of confidence intervals for predictions computed by prvalue and prgen. Because all the examples, datasets, and author-written commands are available from the authors' Web site, readers can easily replicate the concrete examples using Stata, making it ideal for students or applied researchers who want to know how to fit and interpret models for categorical data.