This systematic review investigated one systematic approach to designing, implementing, and evaluating functional assessment–based interventions (FABI) for use in supporting school-age students with or at-risk for high-incidence disabilities. We …
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.
The standardized mean difference (SMD) is surely one of the best known and most widely used effect size metrics used in meta-analysis. In generic terms, the SMD parameter is defined as the difference in population means between two groups (often this difference represents the effect of some intervention), scaled by the population standard deviation of the outcome metric.