title: A d-statistic for single-case designs that is equivalent to the usual between-groups d-statistic.
abstract: 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 analyses in planning new studies and grant proposals, and to meta-analyse effects across studies of the same question. We discuss limitations of this d-statistic, and possible remedies to them. Even so, this d-statistic is better founded statistically than other effect size measures for single-case design, and unlike many general linear model approaches such as multilevel modelling or generalised additive models, it produces a standardised effect size that can be integrated over studies with different outcome measures. SPSS macros for both effect size computation and power analysis are available.
authors.affiliation: a School of Social Sciences, Humanities and Arts , University of California , Merced , CA , USA.
authors.forename: William R
authors.initials: WR
authors.lastname: Shadish
authors.forename: Larry V
authors.initials: LV
authors.lastname: Hedges
authors.forename: James E
authors.initials: JE
authors.lastname: Pustejovsky
authors.forename: Jonathan G
authors.initials: JG
authors.lastname: Boyajian
authors.forename: Kristynn J
authors.initials: KJ
authors.lastname: Sullivan
authors.forename: Alma
authors.initials: A
authors.lastname: Andrade
authors.forename: Jeannette L
authors.initials: JL
authors.lastname: Barrientos
mesh_terms: D006801:Humans; D015201:Meta-Analysis as Topic; D012107:Research Design / Q000706:statistics & numerical data*
keywords: Analysis; Meta-analysis; Single-case designs; Standardised mean difference; d-Statistic