Regression models for categorical dependent variables using Stata

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After reviewing the linear regression model and introducing maximum likelihood estimation, Long extends the binary logit and probit models, presents multinomial and conditioned logit models and describes models for sample selection bias

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Title Statements

Full title :Regression models for categorical dependent variables using Stata / J. Scott Long, Departments of Sociology and Statistics, Indiana University, Bloomington, Indiana, Jeremy Freese, Department of Sociology and Institute for Policy Research, Northwestern University, Evanston, Illinois

Summary

Edition Statements

Publication Date:©2014
Edition:Third edition

Publication Statements

Publisher(s):Stata Press Publication, StataCorp LP
Place of Publication:College Station, Texas
Language:eng
Publication Date:©2014

The Physical Object

Description:xxiii, 589 pages : : illustrations ; : 24 cm

Edition Identifiers

ISBN:9781597181112, 1597181110
oclc:ocn904269323
LC Classification:QA278.2
Dewey Decimal:519.536

Introduction -- Introduction to Stata -- Estimation, testing, and fit -- Methods of interpretation -- Models for binary outcomes : estimation, testing, and fit -- Models for binary outcomes : interpretation -- Models for ordinal outcomes -- Models for nominal outcomes -- Models for count outcomes