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Formula, mlogit and ologit mentioned |
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'''Logistic regression''' is a statistical regression model for binary dependent variables. It can be considered as a [[generalized linear model]]
that utilizes the [[logit]] as its [[link function]].
The model takes the following form:
:<math>log(\frac{p}{1-p}) = \alpha + \beta_1 X_1 + \ldots + \beta_k X_k</math>
The log of the odds (probability divided by one minus the probability) of the outcome is modelled as a linear function of the explanatory variables, X<sub>1</sub> to X<sub>k</sub>.
Extensions of the model exist to cope with multi-category dependent variables and ordinal dependent variables.
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