Regression Models for Categorical and Limited Dependent Variables

Framsida
SAGE, 9 jan. 1997 - 297 sidor

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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Innehåll

Introduction
1
1
3
The Linear Regression Model
11
4
28
The Linear Probability Probit and Logit
34
3
43
8
52
Hypothesis Testing and Goodness of
89
63
161
1
182
The Tobit Model
187
28
191
41
200
Regression Models for Counts
217
43
229
Conclusions
251

4
108
Ordered Logit and Ordered Probit Analysis
114
1
116
3
127
8
142
xi
143
Multinomial Logit and Related Models
148
A Answers to Exercises
264
References
274
Effects of Changing the Slope and Intercept on the Binary
280
Author Index
283
191
296
Upphovsrätt

Vanliga ord och fraser

analysis assume assumption B₁ binary logit censored Chapter chi-square computed consider constraints count models dependent discrete change dummy variables equal errors example exp(xẞ expected value factor change Figure fully standardized given hypothesis independent variables indicated intercept interpreted Labor Force Participation latent variable likelihood function linear regression model log likelihood log-linear models logit and probit logit model LR test M₁ M₂ marginal effect mean measures of fit ML estimator MNLM multinomial logit multinomial logit model NBRM nonlinear normal distribution odds ratio ordered logit ordered logit model ordered probit ordinal outcome overdispersion Panel parallel regression parameters plots Poisson distribution Poisson regression Poisson regression model Pr(y predicted probability prestige probability curve probit model sample slope ẞk standard deviation standardized coefficient statistic Table tobit truncated unit change Var(y variables constant versus Wald test x₁ xẞ y*-standardized z-test

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Om författaren (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.

Bibliografisk information

TitelRegression Models for Categorical and Limited Dependent Variables
Volym 7 av Advanced Quantitative Techniques in the Social Sciences, ISSN 2976-6974
FörfattareJ. Scott Long
Utgåvanytryck
UtgivareSAGE, 1997
ISBN0803973748, 9780803973749
Längd297 sidor
  
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