The logistic regression model uses the logit function to model the probability of a binary outcome. For instance, in cancer research, the outcome could be the presence (1) or absence (0) of cancer. The predictor variables are combined linearly using coefficients that are estimated from the data. The logit function then transforms this linear combination into a probability between 0 and 1.
