Figure 1.

Structure of logistic regression models for diagnosing endometriosis. Logistic regressions calculate the odds and probability of a binary outcome (e.g., positive endometriosis diagnosis) using measurements taken across several predictor variables (e.g., patient observations). The model parameters, the β coefficients, are identified by applying the logistic regression model to a many-patient data set for whom the outcomes are known, and these coefficients can then be used with new patient data to predict the likelihood of endometriosis in that patient.