Quantification of behavioral data with effect sizes and statistical significance tests

Abstract

This article describes the use of statistical significance tests and distance-based effect sizes with behavioral data from single case experimental designs (SCEDs). Such data often are interpreted only with visual analysis. However, a growing movement in the field is to quantify results to improve decision-making and communication across studies and sciences. The goal of the present study was to assess the agreement between visual analysis and various statistical tests. We recruited visual analysts to judge 160 pairwise data sets from published articles and compared these analyses to significance tests and effect sizes. One-tailed significance testing of Tau z and the percentage of pairwise differences in the predicted direction (PWD) generally agreed with each other, and complemented the effect sizes of Ratio of Distances (RD) and g. Visual analysis was somewhat unreliable and should be combined with statistical complements to maximize decision accuracy.