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Regression Models for Categorical and Limited Dependent Variables (Advanced Quantitative Techniques in the Social Sciences) by J Scott Long
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Regression Models for Categorical
and Limited Dependent Variables
(Advanced Quantitative Techniques
in the Social Sciences) by J Scott
Long
Very Very Readable Book
THE APPROACH
J. Scott Long’s approach is…
File Details- Added: May, 12th 2011
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- Regression Models for Categorical and Limited Dependent Variables (Advanced Quantitative Techniques in the Social Sciences) by J Scott Long Very Very Readable Book THE APPROACH 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, 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, University of Kansas THE ORGANIZATION 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 are developed, then estimation issues are considered, then issues of testing and interpretation are considered, then variations and extensions are explored. --Robert L. Kaufman, Sociology, Ohio State University FOR THE COURSE 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 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, 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. Personal Review: Regression Models for Categorical and Limited Dependent Variables (Advanced Quantitative Techniques in the Social Sciences) by J Scott Long This book is especially useful to start understanding topics like ordered probit, multinomial logit, negative binomial regression and zero-inflated count models. Although it starts with a chapter on the linear regression model, it should not be mistaken for an introductory text. I would certainly advise readers with limited background in regression models to start with other books, like the one of Wooldridge (Introductory Econometrics). The quality of this book must be that I've yet to see a book that explains these topics more intuitively. That is not to say it is easy or without mathematics, it's not. It just looks like the mathematics is only used for better comprehension, not to give you the full proof. Furthermore, while reading it you get the feeling that the author understands what you, as a researcher, are interested in. This allows him to focus on the topics of interest, like model selection and testing and interpretation of output. So although this is not a cookbook, it may well be the closest thing to it, especially in combination with his new book on applying these models in Stata (only available at Stata). It is a pity that the author stops short of non-parametric models (next edition?). For More 5 Star Customer Reviews and Lowest Price: Regression Models for Categorical and Limited Dependent Variables (Advanced Quantitative Techniques in the Social Sciences) by J Scott Long 5 Star Customer Reviews and Lowest Price!
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