Offering a clear set of workable examples with data and explanations, Interaction Effects in Linear and Generalized Linear Models is a comprehensive and accessible text that provides a unified approach to interpreting interaction effects.

This text covers the consequences of violating one of the key assumptions of Ordinary Least Squares regression (equal error variances), diagnostic tools to assess the existence of the problem of heteroskedasticity, and statistical techniques to analyse the data correctly.