  Two of the most important extensions of the basic regression model are
moderated effects (due to interactions) and mediated effects (i.e. indirect
effects). Combinations of these effects may also be present. In this work, an
important, yet missing combination is presented that can determine whether a
moderating effect itself is mediated by another variable. This 'indirect
moderation' model can be assessed by a four-step decision tree which guides the
user through the necessary regression analyses in order to infer or refute
indirect moderation. A simple simulation experiment shows how the method
performs under several basic scenarios. Analysis of an empirical data set shows
that the indirect moderation model is extremely valuable in applied research.
