Abstract

This paper argues that while Chambers' method of corresponding regressions offers an intriguing way of analyzing empirical data much remains to be done to make the mathematical, and thus, the statistical meaning of the procedure clear and intuitive. Chambers' theoretical justification of the method of the claim that it can in some sense validate formal cause explanations as alternatives to efficient cause, mechanistic ones is rejected. Chambers has misattributed the mechanistic cast of most contemporary psychological explanations to linear temporality rather than to necessity, and has preserved such necessity in the quality of asymmetry. The paper seeks to distinguish and clarify temporality, causality, and necessity in order to be more clear about the central theoretical problem Chambers identifies. It is further argued that the current theoretical issues facing the discipline likely cannot be resolved by methodological advances