Binary regression: Difference between revisions

Revision as of 17:52, 16 June 2019

Revision as of 19:09, 16 June 2019

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The latent variable interpretation has traditionally been used in [[bioassay]], yielding the [[probit model]], where normal variance and a cutoff are assumed. The latent variable interpretation is also used in [[item response theory]] (IRT).

The simplest direct probabilistic model is the [[logit model]]], which models the [[log-odds]] as a linear function of the explanatory variable or variables. The logit model is "simplest" in the sense of [[generalized linear model]]s (GLIM): the log-odds are the natural parameter for the [[exponential family]] of the Bernoulli distribution, and thus it is the simplest to use for computations.

==References==

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{{statistics-stub}}

[[Category:Generalized linear models]]

[[Category:Regression analysis]]