Linear Probability, Logit, and Probit Models

ISBN-10: 0803921330
ISBN-13: 9780803921337
Edition: 1995
List price: $22.00 Buy it from $15.44
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Description: 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.  More...

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Book details

List price: $22.00
Copyright year: 1995
Publisher: SAGE Publications, Incorporated
Publication date: 11/1/1984
Binding: Paperback
Pages: 96
Size: 5.50" wide x 8.75" long x 0.25" tall
Weight: 0.484
Language: English

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.

Jean-Michel Bismut is professor of mathematics at the Universit� Paris-Sud, Orsay.

Expertise * Prediction Markets * Qualitative and Limited Dependent Variable

The Linear Probability Model
Specification of Nonlinear Probability Models
Estimation of Probit and Logit Models for Dichotomous Dependent Variables
Minimum Chi-Square Estimation and Polytomous Models Summary and Extensions

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