We consider estimation of mixed-effects logistic regression models for longitudinal data when missing outcomes are not missing at random. A typology of missingness mechanisms is presented that ...

In epidemiological studies, continuous covariates often are measured with error and categorical covariates often are misclassified. Using the logistic regression ...

To study the role of genetic factors in the etiology, susceptibility, or severity of disease, several methods are available. In a transmission disequilibrium test, genotypes of cases are compared to ...

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 ...

Dr. James McCaffrey of Microsoft Research demonstrates applying the L-BFGS optimization algorithm to the ML logistic regression technique for binary classification -- predicting one of two possible ...

The data doctor continues his exploration of Python-based machine learning techniques, explaining binary classification using logistic regression, which he likes for its simplicity. The goal of a ...