We describe a standardised mean difference statistic (d) for single-case designs that is equivalent to the usual d in between-groups experiments. We show how it can be used to summarise treatment effects over cases within a study, to do power …
I’m pleased to announce that the Campbell Collaboration has just published a new discussion paper that I wrote with my colleagues Jeff Valentine and Emily Tanner-Smith about between-case standardized mean difference effect sizes for single-case designs.
I am just back from the Institute of Education Sciences 2016 Principal Investigators meeting. Rob Horner had organized a session titled “Single-case methods: Current status and needed directions” as a tribute to our colleague Will Shadish, who passed away this past year.
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.
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.