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Logistic Regression

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 ...
CU Boulder News & Events7y

Regression for Binary and Count Data: Logistic and Poisson Regression

"Logistic and Poisson Regression," Wednesday, November 5: The fourth LISA mini course focuses on appropriate model building for categorical response data, specifically binary and count data. The most ...
JSTOR Daily1y

Mixed Effects Logistic Regression Models for Multiple Longitudinal Binary Functional Limitation Responses with Informative Drop-Out and Confounding by Baseline Outcomes

In the context of analyzing multiple functional limitation responses collected longitudinally from the Longitudinal Study of Aging (LSOA), we investigate the heterogeneity of these outcomes with ...
Nature8y

Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population ...
JSTOR Daily3mon

Categorical Data Analysis: Some Reflections on the Log Linear Model and Logistic Regression. Part I: Historical and Methodological Overview

Peter B. Imrey, Gary G. Koch, Maura E. Stokes, John N. Darroch, Daniel H. Freeman, Jr. and H. Dennis Tolley The literature of log linear models and logistic regression is surveyed from a contemporary ...