Given logistic regression is substantially more computationally efficient than Cox regression in both settings, we propose a two-step approach to GWAS in cohort and case-cohort studies.

To account for such an over-dispersion, we propose to use an additive logistic normal multinomial regression model to associate the covariates to bacterial composition. The model can naturally account ...

Regression can be used on categorical responses to estimate probabilities and to classify.

Laurence D. Robinson, Nicholas P. Jewell, Some Surprising Results about Covariate Adjustment in Logistic Regression Models, International Statistical Review / Revue Internationale de Statistique, Vol.

This article presents a complete demo program for logistic regression, using batch stochastic gradient descent training with weight decay. Compared to other binary classification techniques, logistic ...

Logistic regression enables you to investigate the relationship between a categorical outcome and a set of explanatory variables. The outcome, or response, can be dichotomous (yes, no) or ordinal (low ...

What are the advantages of logistic regression over decision trees? This question was originally answered on Quora by Claudia Perlich.