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Regression Models for Categorical Dependent Variables Using Stata, Second Edition [Paperback]

J. Scott Long , Jeremy Freese
5.0 out of 5 stars  See all reviews (1 customer review)
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Book Description

15 Nov 2005 1597180114 978-1597180115 2
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-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.

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    Product details

    • Paperback: 527 pages
    • Publisher: Stata Press; 2 edition (15 Nov 2005)
    • Language: English
    • ISBN-10: 1597180114
    • ISBN-13: 978-1597180115
    • Product Dimensions: 23.6 x 18.5 x 3 cm
    • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
    • Amazon Bestsellers Rank: 377,019 in Books (See Top 100 in Books)
    • See Complete Table of Contents

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    Most Helpful Customer Reviews
    1 of 1 people found the following review helpful
    5.0 out of 5 stars Expanded horizons 13 April 2010
    I am currently using this book to figure out what kind of analysis to use for a data set. Not only does the author give the intuition behind models, he also spends much time on results interpretation and post-estimation tests, and shows how to graphically present results. The book is very clearly written (while being precise) and I find it really accessible. After having read three other books on the topic I am so happy I found this one, since it communicates how, why and when to use different models more efficiently. A pleasure to read!
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    Most Helpful Customer Reviews on (beta) 4.2 out of 5 stars  5 reviews
    11 of 11 people found the following review helpful
    5.0 out of 5 stars Very good book on how to do categorical analysis using Stata 14 Aug 2006
    By Yin Luo - Published on
    This is a very good book on how to do econometrics on limited dependent variables using Stata. The author also has another book with more theories if you need. A lot of different models (e.g., logit, probit, ordinal, multinomial, and count data) are illustrated and Stata codes are provided. It's an excellent book for applied econometrians. The only thing that is very important but not covered in this book is panel data models on limited dependent variables, e.g., panel logit or panel probit models.
    6 of 6 people found the following review helpful
    5.0 out of 5 stars A must have for applied econometricians 19 Jun 2008
    By Josh Bode - Published on
    This book is undoubtedly the best resource on discrete choice models for applied econometricians. The insights, applications, and tools provided by Long and Freese help not only make sense out of discrete choice models, but are extremely useful for clearly explaining the results to decision-makers untrained in econometrics. Importantly, the book explicitly details the assumptions embedded in each model and the appropriate tests/corrections.

    The book won't teach someone all the nuances of discrete choice models on its own, and the authors point this out from the outset. However, when combined with "Regression Models for Categorical and Limited Dependent Variables" the two books provide an perfectly balanced dose of underlying intuition, math, and applied work insights (plus excellent tools, and the best explanation of maximum likelihood estimator that I have ever come across).

    The prior reviewer is right that this version of the book doesn't cover discrete choice panel models. And, as the authors point out, it also doesn't cover censored/truncated data models. I see this less a shortfall and more as testament of the authors goal to go deeper rather than broader. As it is, the book covers a wide range of topics. That said, I truly look forward to day when they incorporate those topics into the next version(s) of this very pratical book. (Two thumbs...way up)
    2 of 3 people found the following review helpful
    5.0 out of 5 stars Great Book 23 Oct 2009
    By Adam A. Guerrero - Published on
    This book is a must for anybody interested in using Stata to examine categorical and limited dependent variable regression models. I've been keeping this book within an arm's length while writing programs and estimating models for my dissertation and it's been extremely helpful.
    5.0 out of 5 stars THE book for categorical outcomes (but TERRIBLE binding) 10 Dec 2012
    By Chance - Published on
    Format:Paperback|Verified Purchase
    This is the first of several reference books on regression I turn to when dealing with categorical outcome variables. It's a highly readable text, with a good balance of technical detail and straightforward interpretation. If a scholar needs to conduct a binary logit, ordered logit, multinomial logit, Poisson, or negative binomial regression, this is an excellent reference. Dr. Long and Dr. Freese do an excellent job here.

    The same cannot be said of the book's publisher. This book's binding is probably one of the worst I've ever come across. A fellow student recently remarked that she was missing 10 pages of her text. I see another Amazon review suggesting problems with binding. And page 223-224 of my own text has come completely free of the binding. So while the authors do a fantastic job, I'm afraid the same is not true of the publisher. Just a heads-up for potential buyers.
    2 of 8 people found the following review helpful
    1.0 out of 5 stars More than twenty pages are missing!!! 20 Nov 2012
    By zibei - Published on
    Format:Paperback|Verified Purchase
    Can't believe it happened to me during the final exam preparation!
    I just found out pages from 329 to 352 are missing when my categorical class proceed to this charpter 8! I don't know what to do. I am reluctant to return it because I made tons of notes in the previous charpters already! In other words, I personalized this book for three months!

    I don't know how to ask amazon to make this up for me except return.
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