Regression Models for Categorical and Limited Dependent Variables

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SAGE, Jan 9, 1997 - Mathematics - 297 pages
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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.

  

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Contents

Introduction
1
The Linear Regression Model
11
The Linear Probability Probit and Logit
34
Hypothesis Testing and Goodness of Fit
85
Ordered Logit and Ordered Probit Analysis
114
Multinomial Logit and Related Models
148
mial Logit Model With Three Outcomes
174
The Tobit Model
187
Regression Models for Counts
217
Conclusions
251
A Answers to Exercises
264
References
274
Author Index
283
About the Author
297
Copyright

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About the author (1997)

Scott Long is Distinguished Professor and Chancellor's Professor of Sociology and Statistics at Indiana University, Bloomington. He teaches quantitative methods both at Indiana University and at the ICSPR Summer Program. His earlier research examined gender differences in the scientific career. In recent years, he has collaborated with Eliza Pavalko, Bernice Pescsolido, John Bancroft, Julia Heiman and others in studies of health and aging, stigma and mental health, and human sexuality.

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