Single-case experimental designs (SCEDs) are used to study the effects of interventions on the behavior of individual cases, by making comparisons between repeated measurements of an outcome under different conditions. In research areas where SCEDs …
A wide variety of effect size indices have been proposed for quantifying the magnitude of treatment effects in single-case designs. Commonly used measures include parametric indices such as the standardized mean difference, as well as non-overlap …
Varying methods for evaluating the outcomes of single case research designs (SCD) are currently used in reviews and meta-analyses of interventions. Quantitative effect size measures are often presented alongside visual analysis conclusions. Six …
I’m very happy to share that my article “Procedural sensitivities of effect sizes for single-case designs with directly observed behavioral outcome measures” has been accepted at Psychological Methods. There’s no need to delay in reading it, since you can check out the pre-print and supporting materials.
Parker, Vannest, Davis, and Sauber (2011) proposed the Tau-U index—actually several indices, rather—as effect size measures for single-case designs. The original paper describes several different indices that involve corrections for trend during the baseline phase, treatment phase, both phases, or neither phase.
I’ve just posted a new version of my working paper, Procedural sensitivities of effect sizes for single-case designs with behavioral outcome measures. The abstract is below. This version is a major update of an earlier paper that focused only on the non-overlap measures.
Single-case design effect size calculator
Parker, Vannest, Davis, and Sauber (2011) proposed Tau-U as an effect size measure for use in single-case designs that exhibit baseline trend. In their original paper, they actually conceptualize Tau-U as a family of four distinct indices, distinguished by a) whether the index includes an adjustment for the presence of baseline trend and b) whether the index incorporates information about trend during the intervention phase.
Parker and Vannest (2009) proposed non-overlap of all pairs (NAP) as an effect size index for use in single-case research. NAP is defined in terms of all pair-wise comparisons between the data points in two different phases for a given case (i.