Variance explained: Why size does not (always) matter

I examine the role of explaining variance in the construction of explanator y theory. Explaining variance can be an insufficient basis for evaluating a theory (Lieberson, 1985). Starting with this insight, I suggest that model s that provide explanations of variance do not necessarily provide good exp lanations of causal mechanisms. I then explore the utility of process model s anti theories (Mohr, 1982) relative to variance theories. I clarify the r ole of stochastic processes in such model building and discuss the implicat ions of such processes for evaluating explanatory "adequacy." Under some co nditions, explaining variance may be neither a necessary nor a sufficient c ondition for good explanatory theory. I then identify some implications of this argument for developing and analyzing explanatory theory. These argume nts are applied to two examples: (1) meta-analysis and (2) the disposition Versus situation debate (a variant on the nature versus nurture argument) t o illustrate the implications of this process theory point of view.