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.

A popular way to model overdispersed count data, such as the number of falls reported during intervention studies, is by means of the negative binomial (NB) distribution. Classical estimating methods ...

Course TopicsLinear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the ...

Regression is one of the most powerful statistical tools for finding relationships in data. Python makes it easy, and it's much more flexible than a spreadsheet.

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