This post builds on a previous post on Testing Indirect Effects/Mediation in R.
What is mediation? There are many ways to define mediation and mediators. Here’s one way: Mediation is the process by which one variable transmits an effect onto another through one or more mediating variables. For example, as room temperature increases, people get thirstier, and then they drink more water. In this case, thirst transmits the effect of room temperature on water drinking.
Between-Subjects Factors A between-subjects factor refers to independent groups that vary along some dimension. Put another way, a between-subjects factor assumes that each level of the factor represents an independent (i.e., not correlated) group of observations. For example, an experimental factor could represent 2 independent groups of participants who were randomly assigned to either a control or a treatment groupition. In this case, the between-subjects experimental factor assumes that measurements from both groups of participants are not correlated – they are independent.
What is mediation? There are many ways to define mediation and mediators. Here’s one way: Mediation is the process by which one variable transmits an effect onto another through one or more mediating variables. For example, as room temperature increases, people get thirstier, and then they drink more water. In this case, thirst transmits the effect of room temperature on water drinking.
What is an indirect effect?