Regression Models for Categorical and Limited Dependent Variables

Advanced Quantitative Techniques in the Social Sciences #7

by J. Scott Long

A unified treatment of the most useful models for categorical and limited dependent variables (CLDVs) is provided in this book. Throughout, the links among the models are made explicit, and common methods of derivation, interpretation and testing are applied. In addition, the author explains how models relate to linear regression models whenever possible.

Genres: Sociology

328 pages, Hardcover

First published January 9, 1997

Reviews

[Christophe Van · Rating 5 out of 5]

I think this textbook is an excellent introduction to a large set of models for binary, multinominal, count, duration, and censored or truncated data. It is excellent for a survey course on such models or as an introduction to generalized linear modeling tools. The level is that of a second-semester or second-year graduate student in social sciences (sociology, demography, psychology, communications, marketing and management, etc.) who already knows linear regression. For that audience, the book strikes a very good balance of rigor and relevance.

The book is not technical enough to be used in graduate econometrics courses. But I expect the book being very useful as a textbook in advanced undergraduate econometrics courses or as additional reading to graduate economics students trying to get a more practical understanding of how and when to use these models and how to interpret the estimates.

[Siddharth P K · Rating 5 out of 5]

A good primer to get an understanding of the CLDV Regression Models with tonnes of references for further reading and a very intuitive tone.

[Lin · Rating 5 out of 5]

A classic on categorical and limited DV.