Logistic regression is a powerful technique for fitting models to data with a binary response variable, but the models are difficult to interpret if collinearity, nonlinearity, or interactions are ...

Balgobin Nandram, Erik Barry Erhardt, Fitting Bayesian Two-Stage Generalized Linear Models Using Random Samples via the SIR Algorithm, Sankhyā: The Indian Journal of Statistics (2003-2007), Vol. 66, ...

In this module, we will introduce the basic conceptual framework for statistical modeling in general, and linear statistical models in particular. In this module, we will learn how to fit linear ...