ABSTRACT
In this chapter, the authors’ begin with the simple case where one or more continuously measured independent variables varies between the groups of linked observations; in other words, the groups of linked observations are nested under levels of the continuously varying predictors. They seek to the case in which continuous predictors vary within the groups of linked observations. The authors’ examine cases in which the independent variables of interest vary both within and between grouped observations. They provide an introduction to such models, involving multiple random effects that can either be hierarchically nested or crossed. The authors show that one can readily incorporate more or less continuously varying independent variables into the models underlying the analysis of nonindependent observations. They ask about interactions between the gross sales volume of the stores and the independent variables that vary within stores.
