April 29, 2019

A Casual Introduction to the glmulti: An R Package for Easy Automated Model Selection with Generalized Linear Models

Biostatistics Journal Club

Tuesday, May 7th, 2019

12 noon

A Casual Introduction to the glmulti: An R Package for Easy Automated Model Selection with Generalized Linear Models

Presented by
D. Keith Williams, MPH, PhD
Professor, Vice Chair for Education
Department of Biostatistics
University of Arkansas for Medical Sciences

Abstract
This presentation is an introduction to glmulti, an R package for automated model selection and multi-model inference with glm and related functions. From a list of explanatory variables, the provided function glmulti builds all possible unique models involving these variables and, optionally, their pairwise interactions.
Restrictions can be specified for candidate models, by excluding specific terms, enforcing marginality, or controlling model complexity. Models are fitted with standard R functions like glm. The n best models and their support (e.g., (Q)AIC, (Q)AICc, or BIC) are returned, allowing model selection and multi-model inference through standard R functions. The package is optimized for large candidate sets by avoiding memory limitation, facilitating parallelization and providing, in addition to exhaustive screening, and a compiled genetic algorithm method.