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 z(D)) 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 z(D). 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.
Original language | English |
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Pages (from-to) | 318-331 |
Number of pages | 13 |
Journal | Neuropsychology |
Volume | 19 |
Issue number | 3 |
DOIs | |
Publication status | Published - May 2005 |
Keywords
- single-case studies
- statistical methods
- dissociations
- INFERENTIAL METHODS
- SCORE DIFFERENCES
- CONTROL SAMPLE
- T-TEST
- ABNORMALITY
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Assessment of Mood and Cognitive Function
John Crawford (Coordinator), Paul H. Garthwaite (Coordinator) & David C. Howell (Coordinator)
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