Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Logistic regression is often used instead of Cox regression to analyse genome-wide association studies (GWAS) of single-nucleotide polymorphisms (SNPs) and disease outcomes with cohort and case-cohort ...

The LOGISTIC procedure in SAS/STAT software fits linear logistic regression models for binary or ordinal response data by the method of maximum likelihood. Subsets of explanatory variables can be ...

In matched case-control studies, conditional logistic regression is used to investigate the relationship between an outcome of being a case or a control and a set of prognostic factors. When each ...

Food-insecure individuals have fewer total annual visits (in-person and via telehealth) across 4 types of office-based and outpatient visits: general checkup, diagnosis or treatment, psychotherapy or ...

Regression is a statistical tool used to understand and quantify the relation between two or more variables. Regressions range from simple models to highly complex equations. The two primary uses for ...