Comparing a single case to a control sample: testing for neuropsychological deficits and dissociations in the presence of covariates.

Existing inferential methods of testing for a deficit or dissociation in the single case are extended to allow researchers to control for the effects of covariates. The new (bayesian) methods provide a significance test, point and interval estimates of the effect size for the difference between the case and controls, and point and interval estimates of the abnormality of a case's score, or standardized score difference. The methods have a wide range of potential applications, e.g., they can provide a means of increasing the statistical power to detect deficits or dissociations, or can be used to test whether differences between a case and controls survive partialling out the effects of potential confounding variables. The methods are implemented in a series of computer programs for PCs (these can be downloaded from www.abdn.ac.uk/∼psy086/dept/Single_Case_Covariates.htm). Illustrative examples of the methods are provided.