Thomas Metzger - Bayesian Model Selection with the R Package slgf - SatRday Columbus 2020
Channel: SatRday Columbus
Date: 31/12/2020

Bayesian Model Selection with the R Package slgf
Thomas Metzger
Session: Modeling
SatRday Columbus 2020
Nov 14, 2020
https://columbus2020.satrdays.org/

Linear models with categorical predictors are one of the most widely used statistical methods across a variety of scientific fields. However, common simplistic assumptions associated with such linear models may lead to model misspecification and ignore key relationships within the data. With the new R package 'slgf', I implement a model selection approach which utilizes Bayesian statistics to detect structures that would otherwise be disregarded by usual approaches. This R package allows the user to specify a set of candidate models, model structures, and Bayesian priors to quantify the posterior probability of each specified model. I illustrate this method and the usage of slgf through one-way analysis of variance (ANOVA), analysis of covariance (ANCOVA), and unreplicated two-way layouts using real data sets, although slgf is broadly applicable to the class of linear models that includes categorical predictors.

This session is based on joint work with Christopher Franck of Virginia Tech ([Metzger & Franck, 2020](https://www.tandfonline.com/doi/full/10.1080/00401706.2020.1739561)).