Case Selection and Selection Bias in Small-n Research

Abstract

Designing social research is often a blood, toil, sweat and tears experience, with the road to publication usually long and winding. Constantly, the researcher has to weigh different options, and case selection is often considered a particularly delicate and demanding step. For King and colleagues (1994, p. 115), ‘poor case selection can vitiate even the most ingenious attempts, at a later stage, to make valid causal inferences.’ In small-n as well as in large-n approaches ‘the cases you choose affect the answers you get’ (Geddes, 1990). However, case selection usually differs between those two approaches — and for good reasons. Whilst large-n studies generally seek representativeness, for example by random sampling, case selection in small-n research usually follows an intentional logic. Intentional does not, however, mean arbitrary. In the end, the types of cases you select determine which inferences you can draw.

The author thanks the participants of the MZES working group on research design for many vivid and thought-provoking discussions. Many thanks also go to the editors of this volume as well as to Markus Haverland, Guido Schwellnus, Stefan Seidendorf and Stefanie Walter for helpful comments and suggestions.