Le Centre pour l’étude de la citoyenneté démocratique présente :

Atelier métodologique – Go beyond OLS! An introduction to Poisson, Beta, and zero-inflated Beta Bayesian distributional regression

Présentateur : Andrew Heiss, Department of Public Management and Policy at the Andrew Young School of Policy Studies at Georgia State University

Quand : mercredi 13 novembre 2024, 12h30-15h30
Où : Université de Montréal, 3150 rue Jean Brillant, Montréal, Québec

Inscription obigatoire, écrivez à vincent.arel-bundock@umontreal.ca.

While ordinary least squares (OLS) regression is an important method for modeling relationships, it’s not always well-suited for outcome variables that are proportions (bounded between 0–100%) and counts (limited to whole numbers). In this workshop, you’ll learn how to use Bayesian regression techniques to get richer and more detailed information from more specialized types of data. Using R, Stan, {brms}, and {marginaleffects} you’ll learn how to (1) correctly model counts and proportions and (2) process, plot, interpret, and communicate the results.