ABSTRACT
This chapter reviews simple interaction effects: how to specify them, how to interpret them, and how to plot them. It deals with a case of an interaction between a single categorical variable and a single continuous variable. The chapter focuses on to more complex interactions between multiple continuous predictor variables. The golem provides a posterior distribution of plausibility for combinations of parameter values. The evidence from surviving manatees and bombers is misleading, because it is conditional on survival. Manatees and bombers that perished look different. Common sorts of multilevel models are essentially massive interaction models, in which estimates are conditional on clusters in the data. Multilevel interaction effects are complex. Models that allow for complex interactions are easy to fit to data.
