9780803921337

Linear Probability, Logit, and Probit Models

by
  • ISBN13:

    9780803921337

  • ISBN10:

    0803921330

  • Format: Paperback
  • Copyright: 1984-11-01
  • Publisher: Sage Publications, Inc

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Supplemental Materials

What is included with this book?

Summary

Ordinary regression analysis is not appropriate for investigating dichotomous or otherwise "limited" dependent variables, but this volume examines three techniques -- linear probability, probit, and logit models -- which are well-suited for such data. It reviews the linear probability model and discusses alternative specifications of non-linear models. Using detailed examples, Aldrich and Nelson point out the differences among linear, logit, and probit models, and explain the assumptions associated with each.

Table of Contents

Series Introduction 5(2)
Acknowledgments 7(2)
The Linear Probability Model
9(21)
Introduction
9(1)
Review of the Multivariate, Linear Regression Model
10(2)
A Dichotomous Dependent Variable and the Linear Probability Model
12(8)
A Dichotomous Response Variable with Replicated Data
20(2)
Polytomous or Multiple Category Dependent Variables
22(2)
The Linearity Assumption
24(3)
The Effect of an Incorrect Linearity Assumption
27(3)
Specification of Nonlinear Probability Models
30(18)
Introduction
30(1)
The General Problem of Specification
30(1)
Alternative Nonlinear Functional Forms for the Dichotomous Case
31(4)
Derivation of Nonlinear Transformations from a Behavioral Model
35(2)
Nonlinear Probability Specifications for Polytomous Variables
37(3)
Behavior of the Logit and Probit Specifications
40(7)
Summary
47(1)
Estimation of Probit and Logit Models for Dichotomous Dependent Variables
48(18)
Introduction
48(1)
Assumptions of the Models
48(1)
Maximum Likelihood Estimation
49(3)
Properties of Estimates
52(2)
Interpretation of and Inference from MLE Results
54(11)
Conclusions
65(1)
Minimum Chi-Square Estimation and Polytomous Models
66(12)
Introduction
66(1)
Minimum Chi-Square Estimation for Replicated, Dichotomous Data
67(6)
Polytomous Dependent Variables
73(5)
Summary and Extensions
78(7)
Introduction
78(1)
Summary
78(3)
Extensions
81(4)
Notes 85(8)
References 93(2)
About the Authors 95

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