Comparison of Overlap Methods for Quantitatively Synthesizing Single-Subject Data

Abstract

Four overlap methods for quantitatively synthesizing single-subject data were compared to visual analysts’ judgments. The overlap methods were percentage of nonoverlapping data, pairwise data overlap squared, percentage of data exceeding the median, and percentage of data exceeding a median trend. Visual analysts made judgments about 160 A-B data sets selected randomly from the Journal of Applied Behavior Analysis . The four overlap methods were compared for data sets in which all visual analysts agreed a change in data occurred or a change did not occur across conditions. Each overlap method had unacceptably high levels of errors. Given the findings and weaknesses of the overlap methods, their use should be abandoned. The desirable characteristics of a quantitative synthesis method are described.