Abstract
In contrast to the standard use of regression, in which an individual's score on the dependent variable is unknown, neuropsychologists are often interested in comparing a predicted score with a known obtained score. Existing inferential methods use the standard error for a new case (SN+1) to provide confidence limits on a predicted score and hence are tailored to the standard usage. However, SN+1 can be used to test whether the discrepancy between a patient's predicted and obtained scores was drawn from the distribution of discrepancies in a control population. This method simultaneously provides a point estimate of the percentage of the control population that would exhibit a larger discrepancy. A method for obtaining confidence limits on this percentage is also developed. These methods can be used with existing regression equations and are particularly useful when the sample used to generate a regression equation is modest in size. Monte Carlo simulations confirm the validity of the methods, and computer programs that implement them are described and made available.
Original language  English 

Pages (fromto)  259271 
Number of pages  12 
Journal  Neuropsychology 
Volume  20 
DOIs  
Publication status  Published  2006 
Keywords
 neuropsychological assessment
 regression equations
 singlecase methods
 TRUAX RELIABLE CHANGE
 CLINICAL NEUROPSYCHOLOGY
 CLASSICAL APPROACH
 STANDARD ERROR
 WAISR
 INDEX
 PERFORMANCE
 JACOBSON
Impacts

Assessment of Mood and Cognitive Function
John Crawford (Coordinator), Paul H. Garthwaite (Coordinator) & David C. Howell (Coordinator)
Impact