In ANOVA models, causes (IVs) are often called factors or effects. SEMs use the effects language, and the types of effects can be informative. A direct effect is a causal arrow directly from one variable to another. With an indirect effect, the effect of one variable on another is through a third variable. For example, in Figure 43 above, variable 1 has a direct effect on variable 2, but variable 1 has an indirect effect on variable 3 (because it flows through variable 2). The total effect, as you probably guessed, is equal to the direct plus the sum of indirect effects on a variable.
Last Modified: 02/14/2019