Abstract
Abstract The use of single-case research designs for the evaluation of experimental outcomes is a distinguishing characteristic of applied behavior analysis. Behavior analysts traditionally rely on visual inspection of graphed data in lieu of statistical analyses. Proponents of visual inspection claim lower Type I error rates relative to statistical analysis. However, behavior analysts also employ response guided experimentation (i.e., allowing accumulating data to guide the further course of the experiment). Based on data published by Matyas and Greenwood (1990), we argue that when visual inspection is combined with response guided experimentation, Type I error rates could easily be as high as 25%. Tables of error rates as a function of alphas, autocorrelation, and number of looks are presented. We suggest caution in interpreting conclusions based on single case designs employing visual analysis and response guided experimentation.
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