Linear Probability, Logit, and Probit Models
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A01=Forrest D. Nelson
A01=John Aldrich
Author_Forrest D. Nelson
Author_John Aldrich
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QASS
Quantitative Applications in the Social Sciences
Quantitative/Statistical Research
QuantitativeStatistical Research
Regression & Correlation
Sociological Research Methods
Product details
- ISBN 9780803921337
- Weight: 140g
- Dimensions: 139 x 215mm
- Publication Date: 21 Feb 1985
- Publisher: SAGE Publications Inc
- Publication City/Country: US
- Product Form: Paperback
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After showing why ordinary regression analysis is not appropriate in investigating dichotomous or otherwise "limited" dependent variables, this volume examines three techniques-linear probability, probit, and logit models-well-suited for such data. It reviews the linear probability model and discusses alternative specifications of nonlinear models.
John H. Aldrich is Pfizer-Pratt University Professor of Political Science at Duke University. He is author of Why Parties: A Second Look (2011), coeditor of Positive Changes in Political Science (2007), and author of Why Parties (1995) and Before the Convention (1980). He is a past president of both the Southern Political Science Association and the Midwest Political Science Association and is serving as president of the American Political Science Association. In 2001 he was elected a fellow in the American Academy of Arts and Sciences.
Expertise
* Prediction Markets
* Qualitative and Limited Dependent Variable
