Multiple Regression in Small-N Comparisons

Abstract

Michael Shalev has turned his attention, once again, to the bad methodological habits that social scientists – like myself – often adopt. As always, he presents us with thoughtful, rigorous, and penetrating criticism, but also with a generous dose of constructive prescription. His target is the widespread use of regression techniques in cross-national comparative research. The gist of the argument is that multiple regression (MR) is a far too blunt instrument if our aim is to arrive at a robust identification of crucial causal mechanisms. MR, as he puts it (p. 42), renders the cases invisible and, hence, precludes researchers from having any dialogue with them. The case becomes a set of scores; the causal mechanisms are reduced to correlation coefficients. As a result, analytical power is sacrificed rather than gained. Shalev advocates simpler ‘low-tech’ approaches such as tabular representations, tree diagrams, or clustering techniques either as substitutes for, or as companions to, regression analysis.

Citation

Esping-Andersen, G. (2007), "Multiple Regression in Small-N Comparisons", Mjøset, L. and Clausen, T.H. (Ed.) Capitalisms Compared (Comparative Social Research, Vol. 24), Emerald Group Publishing Limited, Leeds, pp. 335-342. https://doi.org/10.1016/S0195-6310(06)24009-2