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Inferential methods for comparing two single cases

Crawford, John R.; Garthwaite, Paul H. and Wood, Liam T. (2010). Inferential methods for comparing two single cases. Cognitive Neuropsychology, 27(5) pp. 377–400.

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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 Compare_Two_Cases.htm).

Item Type: Journal Article
Copyright Holders: 2011 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business
ISSN: 1464-0627
Keywords: single-case methods; Bayesian statistics; dissociations; neuropsychological methods; credible limits; multiple indicators
Academic Unit/Department: Mathematics, Computing and Technology > Mathematics and Statistics
Mathematics, Computing and Technology
Item ID: 33027
Depositing User: Emma Howard
Date Deposited: 01 Mar 2012 16:04
Last Modified: 18 Jan 2016 13:58
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