In
statistics, the
ordered logit model (also
ordered logistic regression or
proportional odds model), is a
regression model for ordinal
dependent variables. For example, if one question on a survey is to be answered by a choice among "poor", "fair", "good", "very good", and "excellent", and the purpose of the analysis is to see how well that response can be predicted by the responses to other questions, some of which may be quantitative, then ordered logistic regression may be used. It can be thought of as an extension of the
logistic regression model that applies to
dichotomous dependent variables, allowing for more than two (ordered) response categories.