Within-subjects designs: To use or not to use?

This article considers the several factors pertinent to deciding whether a within- or between-subjects design should be employed for a research application. A general principle favoring within-subjects designs is the statistical efficiency afforded by removing subject variance from error terms used to test treatment effects. Within-subjects designs, however, are often faulted for being subject to context effects of practice, sensitization, and carry-over that may limit interpretation of results. At the same time, between-subjects designs are not devoid of context effects, but rather have #the context that a single treatment affords itself. Since ecological validity of results depends on the correspondence of the research context to the generalization context, within-subjects designs may he preferred when the generalization context includes the equivalent of several concurrent treatments. The discussion focuses additionally on (a) procedures to minimize practice, sensitization and carry-over effects in within-subjects designs when they a;e not desired, and (b) means of using these effects to advantage in research. Frequently an investigator faces the choice of whether to examine the effects of two or more experimental treatments by exposing each subject to (a) only a single treatment (between-subjects design) or (b) several or all of the treatments (within-subjects or re-peated-measures design). Grice ( 19.66) has pointed out that the pattern of treatment ef-fects obtained may vary considerably between the two types of designs. However, only rarely does an investigator make a choice of type of design after consideration of the appropri-ateness of each type to the problem being investigated. I attempt to assemble here sev-eral considerations that may often be ap-propriate to the decision between a within-or between-subjects design. Nthough they are mentioned briefly, sta-tistical considerations relating to choice of design are not of primary interest here. These statistical matters are well handled in stan-dard statistical texts, as referenced below. My aim, rather, is to detail the psychological considerations that are critical to the choice