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 ...
A class of conditional logistic regression models for clustered binary data is considered. This includes the polychotomous logistic model of Rosner (1984) as a special case. Properties such as the ...
"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 ...
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 beta-binomial distribution is extended to allow negative correlations among binary variates within an experimental unit. Regression models are proposed for both the binary variate response rate ...
Increased triglyceride-glucose (TyG) index values are strongly associated with decreased lung function in healthy individuals.
Researchers used 2018 data from the National Health Interview Survey to investigate the association. Men taking anxiety and depression medications were more likely to undergo prostate specific antigen ...
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