Linear Probability, Logit, and Probit Models

by Aldrich


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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Bibliographic Information
  • English
  • 9780803921337 / 0803921330
  • United Kingdom
  • Paperback
  • Pages: 95
  • SAGE Publications Inc. / Sage
  • Readership: Professional and Scholarly
  • Publish State: Published
  • Responsibility: John H. Aldrich and Forrest D. Nelson.
  • Page size: 22
  • Illustration: Illustrations
  • Series: Quantitative Applications in the Social Sciences
  • Reference Code: BDZ0000095125