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Linear Probability, Logit, and Probit Models

Om Linear Probability, Logit, and Probit Models

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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  • Språk:
  • Engelska
  • ISBN:
  • 9780803921337
  • Format:
  • Häftad
  • Sidor:
  • 96
  • Utgiven:
  • 21. februari 1985
  • Mått:
  • 142x216x5 mm.
  • Vikt:
  • 118 g.
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Leveranstid: 2-4 veckor
Förväntad leverans: 27. november 2024

Beskrivning av Linear Probability, Logit, and Probit Models

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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