Mycroft, Mitchell, and Kay (2002) have criticised existing inferential methods (e.g., Crawford & Howell, 1998) for comparing a single case with a control sample and propose that such comparisons be made using a modified ANOVA. It is argued that the assumptions made by Mycroft et al. are questionable and, even if they held, would not invalidate Crawford and Howell's method. Crawford and Howell's null hypothesis is that the patient is an observation from the control population whereas Mycroft et al.'s null hypothesis is that the control population and a notional population of patients have a common mean. Even if one accepts Mycroft et al.'s conceptualisation, their arguments only have force if (1) the variance of a notional population of patients was larger than that of the control population, and (2) patients with impaired performance were balanced exactly by patients whose performance had been enhanced relative to controls. Furthermore, the modified ANOVA would have the undesirable consequence of reducing statistical power unnecessarily and it requires users to provide some estimate of the variance of a hypothetical population.
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http://dx.doi.org/10.1080/02643290342000276 | DOI Listing |
Cogn Neuropsychol
September 2006
University of Aberdeen, Aberdeen, UK.
Testing for the presence of a deficit by comparing a case to controls is a fundamental feature of many neuropsychological single-case studies. Monte Carlo simulation was employed to study the statistical power of two competing approaches to this task. The power to detect a large deficit was low to moderate for a method proposed by Crawford and Howell (1998; ranging from 44% to 63%) but was extremely low for a method proposed by Mycroft, Mitchell, and Kay (2002; ranging from 1% to 13%).
View Article and Find Full Text PDFMycroft, Mitchell, and Kay (2002) have criticised existing inferential methods (e.g., Crawford & Howell, 1998) for comparing a single case with a control sample and propose that such comparisons be made using a modified ANOVA.
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