Adding subjects or adding measurements: Which increases the precision of longitudinal research?

When designing repeated measurement studies, researchers must strike a balance between increasing the number of subjects and increasing the number of measurement times for each subject. The question often becomes "Do I gain more statistical precision by adding subjects or by adding additional follow-up measurements?" This study presents a method for evaluating the relative benefit of adding subjects versus adding measurement times. We used the standard error of estimate (SE) for mean change as the criterion of precision. An existing dataset on post-stroke patients containing six follow-up assessments of six standard rating scales was used. SE values for two common change indices were found and compared for all possible two, three, four, five, and six repeated measurements. Sample sizes required to achieve the same benefit as adding an additional measurement are presented. These data suggest that collecting five or six repeated measurements may be sufficient for accurately assessing change and that attempts to further precision should be accomplished by increasing the sample size.