"J. Scott Long's approach is one that I highly commend. There is a decided emphasis on the application
and interpretation of the specific statistical techniques. Long works from the premise that the major difficulty
with the analysis of limited and categorical dependent variables (LCDVs) is the complexity of interpreting nonlinear
models, and he provides tools for interpretation that can be widely applied across the different techniques."
--Robert L. Kaufman, Sociology, The Ohio State University
"A thorough and comprehensive introduction to analyzing categorical and limited dependent variables from a
traditional regression perspective that provides unusually clear discussions concerning estimation, identification,
and the multiplicity of models available to the researcher to analyze such data."
--Scott Hershberger, Psychology, The University of Kansas
"The thing that impresses me the most about this book is how organized it is. The chapters are in excellent
logical sequence. There is a useful repetition of important concepts (e.g., estimation, hypothesis testing) from
chapter to chapter. J. Scott Long has done a terrific job of organizing like things from disparate literatures,
such as the scaler measures of fit in Chapter 4."
--Herbert L. Smith, Sociology, University of Pennsylvania
"A major strength of the book is the way that it is organized. The chapter about each technique is written
in a highly organized and parallel format. First the statistical basis and assumptions for the particular model
is developed, then estimation issues are considered, then issues of testing and interpretation are considered,
then variations and extensions are explored."
--Robert L. Kaufman, Sociology, The Ohio State University
"I have been teaching a course on categorical data analysis to sociology graduate students for close to 20
years, but I have never found a book with which I was happy. J. Scott Long's book, on the other hand, is nearly
ideal for my objectives and preferences, and I expect that many other social scientists will feel the same way.
I will definitely adopt it the next time I teach the course. It deals with the right topics in the most desirable
sequence and it is clearly written."
--Paul D. Allison, Sociology, University of Pennsylvania
Sage Publications Incorpoated Web Site, September, 2000
Summary
Class tested at two major universities and written by an award-winning teacher, J. Scott Long's book gives readers
unified treatment of the most useful models for categorical and limited dependent variables (CLDVs). Throughout
the book, the links among models are made explicit, and common methods of derivation, interpretation, and testing
are applied. In addition, Long explains how models relate to linear regression models whenever possible. In order
for the reader to see how these models can be applied, Long illustrates each model with data from a variety of
applications, ranging from attitudes toward working mothers to scientific productivity.
The book begins with a review of the linear regression model and an introduction to maximum likelihood estimation.
It then covers the logit and probit models for binary outcomes--providing details on each of the ways in which
these models can be interpreted--and reviews standard statistical tests associated with maximum likelihood estimation
and considers a variety of measures for assessing the fit of a model. Long extends the binary logit and probit
models to ordered outcomes, presents the multinomial and conditioned logit models for nominal outcomes, and considers
models with censored and truncated dependent variables with a focus on the tobit model. He also describes models
for sample selection bias and presents models for count outcomes by beginning with the Poisson regression model
and showing how this model leads to the negative binomial model and zero inflated count models. He concludes by
comparing and contrasting the models from earlier chapters and discussing the links between these models and models
not discussed in the book, such as loglinear and event history models. Helpful exercises are included in the book
with brief answers included in the appendix so that readers can practice the techniques as they read about them.
