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" 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
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BL
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| Record Number
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591715
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| Doc. No
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b420934
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| Main Entry
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Long, J. Scott
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| Title & Author
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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
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| Edition Statement
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Third edition
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| Page. NO
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xxiii, 589 pages :: illustrations ;; 24 cm
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| ISBN
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9781597181112
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: 1597181110
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| Bibliographies/Indexes
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Includes bibliographical references (pages 561-568) and indexes
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| Contents
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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
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| Abstract
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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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| Subject
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Regression analysis
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| Subject
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Social sciences-- Statistical methods-- Data processing
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| Subject
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Stata
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| Dewey Classification
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519.536
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| LC Classification
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QA278.2.L66 2014
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| Added Entry
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Freese, Jeremy
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