Inferential methods for comparing two single cases

J. R. Crawford, P. H. Garthwaite, L. T. Wood

Research output: Contribution to journalArticlepeer-review

47 Citations (Scopus)


In neuropsychological single-case studies, it is not uncommon for researchers to compare the scores of two single cases. Classical (and Bayesian) statistical methods are developed for such problems, which, unlike existing methods, refer the scores of the two single cases to a control sample. These methods allow researchers to compare two cases' scores, with or without allowing for the effects of covariates. The methods provide a hypothesis test (one- or two-tailed), point and interval estimates of the effect size of the difference, and point and interval estimates of the percentage of pairs of controls that will exhibit larger differences than the cases. Monte Carlo simulations demonstrate that the statistical theory underlying the methods is sound and that the methods are robust in the face of departures from normality. The methods have been implemented in computer programs, and these are described and made available (to download, go to
Original languageEnglish
Pages (from-to)377-400
Number of pages24
JournalCognitive Neuropsychology
Issue number5
Publication statusPublished - 2010


  • single-case methods
  • Bayesian statistics
  • dissociations
  • neuropsychological methods
  • credible limits
  • multiple indicators


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