A d-statistic for single-case designs that is equivalent to the usual between-groups d-statistic

William R. Shadish*, Larry V. Hedges, James E. Pustejovsky, Jonathan G. Boyajian, Kristynn J. Sullivan, Alma Andrade, Jeannette L. Barrientos

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

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 metaanalyse 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.

Original languageEnglish (US)
Pages (from-to)528-553
Number of pages26
JournalNeuropsychological rehabilitation
Volume24
Issue number3-4
DOIs
StatePublished - 2014

Keywords

  • Analysis
  • D-statistic
  • Meta-analysis
  • Single-case designs
  • Standardised mean difference

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Rehabilitation
  • Arts and Humanities (miscellaneous)
  • Applied Psychology

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