# Chapter 10 Model Building

Model building methods are used mainly in exploratory situations where many independent variables have been measured, but a final model explaining the dependent variable has not been reached. You want to build a model that contains enough covariates to explain the model well, but still be parsimonious such that the model is still interpretable.

This chapter introduces how to use and interpret different types of covariates, how to choose covariates, and then cover some methods to compare between competing models using measures of model fit.

This section uses functions from the gtsummary and survey packages to help tidy and visualize results from regression models. It also uses functions from the performance and glmnet packages to perform model selection and assessment.