title: Testing for suspected impairments and dissociations in single-case studies in neuropsychology: evaluation of alternatives using monte carlo simulations and revised tests for dissociations.
abstract: In neuropsychological single-case studies, a patient is compared with a small control sample. Methods of testing for a deficit on Task X, or a significant difference between Tasks X and Y, either treat the control sample statistics as parameters (using z and zD) or use modified t tests. Monte Carlo simulations demonstrated that if z is used to test for a deficit, the Type I error rate is high for small control samples, whereas control of the error rate is essentially perfect for a modified t test. Simulations on tests for differences revealed that error rates were very high for zD. A new method of testing for a difference (the revised standardized difference test) achieved good control of the error rate, even with very small sample sizes. A computer program that implements this new test (and applies criteria to test for classical and strong dissociations) is made available.
authors.affiliation: School of Psychology, University of Aberdeen, Aberdeen, Scotland. j.crawford@abdn.ac.uk
authors.forename: John R
authors.initials: JR
authors.lastname: Crawford
authors.forename: Paul H
authors.initials: PH
authors.lastname: Garthwaite
mesh_terms: D003198:Computer Simulation; D004213:Dissociative Disorders / Q000503:physiopathology*; D005069:Evaluation Studies as Topic; D006801:Humans; D009010:Monte Carlo Method; D009484:Neuropsychology; D018401:Sample Size; D012847:Single Person