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Linear Probability, Logit, and Probit Models

Bag 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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  • Sprog:
  • Engelsk
  • ISBN:
  • 9780803921337
  • Indbinding:
  • Paperback
  • Sideantal:
  • 96
  • Udgivet:
  • 21. februar 1985
  • Størrelse:
  • 142x216x5 mm.
  • Vægt:
  • 118 g.
  • BLACK FRIDAY
    : :
Leveringstid: 2-4 uger
Forventet levering: 21. december 2024
Forlænget returret til d. 31. januar 2025

Beskrivelse af 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.

Brugerbedømmelser af Linear Probability, Logit, and Probit Models



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