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 ...

Health Insurance Equity, Social Determinants, Socioeconomic Status, Insurance Quality, Urban-Rural Disparity, Hukou, China ...