Multiple Logistic Regression and Model Fit Multiple Logistic Regression

Abstract

Multiple Logistic Regression Just as in OLS regression, logistic models can include more than one predictor. The analysis options are similar to regression. One can choose to select variables, as with a stepwise procedure, or one can enter the predictors simultaneously, or they can be entered in blocks. Variations of the likelihood ratio test can be conducted in which the chi-square test (G) is computed for any two models that are nested. Nested models are models in which only a subset of predictors from the full model are included. A chi-square test is not valid unless the two models compared involve one model that is a reduced form of (i.e., nested within) the other model. In particular, the two models must be based on the same set of cases.