Regression Models for Categorical Dependent Variables Using Stata, Third Edition

by J. Scott Long, Jeremy Freese

Regression Models for Categorical Dependent Variables Using Stata, Third Edition , by J. Scott Long and Jeremy Freese, is an essential reference for those who use Stata to fit and interpret regression models for categorical data. Although regression models for categorical dependent variables are common, few texts explain how to interpret such models; this text decisively fills the void.

1154 pages, Kindle Edition

First published January 1, 2001

Reviews

[Connor Oswald · Rating 4 out of 5]

Really solid manual on categorical regression models. Easy to go through with examples along the way.

[Marks54 · Rating 4 out of 5]

I do not normally review manuals/texts like this but I am going through this for a large current project and have found it to be exceptionally useful for getting up to speed on these odd models on STATA.

[Rachel · Rating 5 out of 5]

This book is less useful as an introduction to regression models and more useful as a reference when performing different regressions in Stata.

[Juan Gonzalez · Rating 5 out of 5]

Un libro genial para aprender a hacer distintos tipos de regresiones en Stata. Lo mejor es acompañarlo con la lectura de Microeconometrics de Cameron & Trivedi para ver un poco más de trasfondo estadístico y comparar entre modelos.

[Lissa · Rating 4 out of 5]

A helpful and detailed book, but the downloadable mtable command for predicted probabilities in Stata was quirky. It worked best (without errors) when most rows were displayed as their own table. I would recommend that when using the mtable command, number and specifically label each "row" as the command sometimes displayed the rows out of order or with duplicates in a table, making it hard to tell which predicted probability was for what variable categories. Another quirk was that when mtable is installed, you can no longer use the older probability commands, so that was an unexpected pain.

Other than mtable, I have no complaints. Since I was just doing logistic and multinomial logistic regression for my dissertation, I didn't delve too deeply into other sections of the book. A class I TA'd for did use the text and the students seemed to find it helpful. They just used it for logistic regression.

[Isabelrt · Rating 5 out of 5]

I have the 1st edition, so it may be slightly different. Still, a most useful book. Clear and to the point, with enough theoretical references so you may look up what you need, but sticking to the "how to" of things. Good examples and clear explanations. The best book I ever bought in grad school.

[Stephen Cranney · Rating 4 out of 5]

It simultaneously explains both the theoretical background behind the statistical procedures and the Stata syntax involved to execute the procedures; so it's perfect for people wanting to learn the methods for practical analytical purposes.

[Star]

statistical analysis

[Asif · Rating 5 out of 5]

Best book for categorical dependent variables. I gained alot from it.

[Sultan Almalki · Rating 5 out of 5]

One of the best references I've read about analysing categorical dependent variables using STATA. Simple, comprehensive and nicely structured.

[Lin · Rating 5 out of 5]

Very good read on the subject. Very helpful!