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Paperback

Linear Probability, Logit and Probit Models

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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.

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MORE INFO
Format
Paperback
Publisher
SAGE Publications Inc
Country
United States
Date
1 November 1984
Pages
96
ISBN
9780803921337

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.

Read More
Format
Paperback
Publisher
SAGE Publications Inc
Country
United States
Date
1 November 1984
Pages
96
ISBN
9780803921337