Analyzing Single-Case Data: The Power of Randomization Tests

Abstract

Randomization tests have been proposed as a valid method for analyzing the data of single-case designs. In this study, the power of randomization tests was systematically examined for typical designs that rely on the random assignment of interventions within the sequence of observations. A 30-observation AB design, a 32-observation ABAB design, and a multiple-baseline AB design with 15 observations on each of four individuals were studied. Four levels of autocorrelation were considered, as well as six effect sizes, ranging from 0.0 to 1.4. For each combination of design, autocorrelation, and effect size, power was estimated by generating data for 1,000 experiments. The power estimates were generally found to be low.

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