Stuart R. Lipsitz, Garrett M. Fitzmaurice, Geert Molenberghs, Lue Ping Zhao, Quantile Regression Methods For Longitudinal Data with Drop-Outs: Application to CD4 Cell Counts of Patients Infected with ...

Course Topics"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 ...

A new study investigated how logistic regression model training affects performance, and which features are best to include when examining datasets from individuals suffering from COVID-19.

In this article, we discuss using median regression models to deal with longitudinal data with dropouts. Weighted estimating equations are proposed to estimate the median regression parameters for ...

In many applications, the response variable is not Normally distributed. GLM can be used to analyze data from various non-Normal distributions. In this short course, we will introduce two most common ...

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

Nonlinear regression is a form of regression analysis in which data fit to a model is expressed as a mathematical function.