Lucy Training: Generalized Linear Regression in R - Part 1


Location: 246 Hesburgh Library (View on map )

Presenter: Brian Fogarty

This workshop focuses on techniques when your outcome variable is not continuous or normally distributed. Such outcome variables are considerably more common in social science data than normally distributed outcome variables. We will examine binary and ordered outcome variable regression models in this workshop. (Part 2 of the workshop will be in the Spring 2023 semester and feature nominal and count outcome variable regression models.)

The topics covered during the workshop include:

  • Binary outcome models (logit/probit)
  • Ordered outcome models (ordered logit/probit)

  • Statistical significance and regression coefficient interpretation

  • Visualizations of regression coefficients

The workshop is designed for individuals with experience using generalized linear regression in other statistical software (e.g., Stata, SPSS) and who want to learn how to run generalized linear regression models in R. Further, it is assumed that individuals have a basic understanding of R. We will also be using R Markdown, but it is not critical for learning the material.

This workshop will be offered in-person in Hesburgh Library. There is a limit of 15 participants for this workshop.  Register Now!   
Registration must be completed by Friday, November 11th.

More details about the workshop can be found here.

Originally published at