Linear Probability, Logit, and Probit Models (Quantitative...

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Linear Probability, Logit, and Probit...

Linear Probability, Logit, and Probit Models (Quantitative Applications in the Social Sciences)

John H. Aldrich, Forrest D. Nelson

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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.

カテゴリー:

Mathematics

年:

1984

出版社:

Sage Publications, Inc

言語:

english

ページ:

106

ISBN 10:

0803921330