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Regression Models for Categorical Dependent Variables Using Stata by J. Scott Long ; Jeremy Freese is a nonfiction available to read on EtoBox.

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Although regression models for categorical dependent variables are common, few texts explain how to interpret such models. Regression Models for Categorical Dependent Variables Using Stata, Second Edition, fills this void, showing how to fit and interpret regression models for categorical data with Stata. The authors also provide a suite of commands for hypothesis testing and model diagnostics to accompany the book. The book begins with an excellent introduction to Stata and then provides a general treatment of estimation, testing, fit, and interpretation in this class of models. It covers in detail binary, ordinal, nominal, and count outcomes in separate chapters. The final chapter discusses how to fit and interpret models with special characteristics, such as ordinal and nominal independent variables, interaction, and nonlinear terms. One appendix discusses the syntax of the author-written commands, and a second gives details of the datasets used by the authors in the book. Nearly 50% longer than the previous edition, the book covers new topics for fitting and interpreting models included in Stata 9, such as multinomial probit models, the stereotype logistic model, and zero-trunc

Who reads Regression Models for Categorical Dependent Variables Using Stata?

Author

J. Scott Long ; Jeremy Freese

Publisher

Stata Press

Published

2001

Language

EN

ISBN

9781881228622

Category

nonfiction

Subjects

Mathematics, Social Science, Stem

Rating

4.16 / 5 (37 ratings)

Updated

2026-03-14