Generic to perform multiple functions i.e., fit simple and multiple logistic regression models. Provide options for dealing with missing data e.g., include in output or suppress. For survey data allow ...

Binary Logistic Regression: Binary logistic regression is employed when the dependent variable has only two outcomes—in this case, the dependent variable is referred to as a dichotomous variable.

Learn how to interpret multiple linear regression with more than two independent variables, and what to look for in the output. Find out how to check assumptions, read coefficients, measure fit ...

Multiple Logistic Regression is a statistical technique used to model the relationship between a categorical dependent variable (binary or multi-class) and multiple independent variables (continuous ...

In recent columns we showed how linear regression can be used to predict a continuous dependent variable given other independent variables 1,2. When the dependent variable is categorical, a common ...

Binary logistic regression models are commonly used to assess the association between outcomes and covariates. Many covariates are inherently continuous, and have a variety of distributions, including ...

Objectives This study investigated what clinical and sociodemographic factors affected Wisconsin Card Sorting Test (WCST) factor scores of patients with schizophrenia to evaluate parameters or items ...