Hostname: page-component-848d4c4894-ndmmz Total loading time: 0 Render date: 2024-05-21T22:40:02.872Z Has data issue: false hasContentIssue false

Test–retest bias, reliability, and regression equations for neuropsychological measures repeated over a 12–16-week period

Published online by Cambridge University Press:  27 July 2001

MARTIN C. SALINSKY
Affiliation:
Department of Neurology, Oregon Health Sciences University Epilepsy Center, Portland, Oregon
DANIEL STORZBACH
Affiliation:
Department of Psychiatry, Portland Veterans Affairs Medical Center, Portland, Oregon
CARL B. DODRILL
Affiliation:
Department of Neurology, University of Washington Epilepsy Center, Seattle, Washington
LAURENCE M. BINDER
Affiliation:
Department of Neurology, Oregon Health Sciences University Epilepsy Center, Portland, Oregon

Abstract

The interpretation of neurobehavioral change over time requires knowledge of the test–retest characteristics of the measures. Without this information it is not possible to distinguish a true change (i.e., one reflecting the occurrence or resolution of an intervening process) from that occurring on the basis of chance or systematic bias. We tested a group of 72 healthy young to middle aged adults twice over a 12-to-16-week interval in order to observe the change in scores over time when there was no known intervention. The test battery consisted of seven commonly used cognitive measures and the Profile of Mood States (POMS). Test–retest regression equations were calculated for each measure using initial performance, age, education, and a measure of general intellectual function (Wonderlic Personnel Test) as regressors. Test–retest correlations ranged from .39 (POMS Fatigue) to .89 (Digit Symbol). Cognitive measures generally yielded higher correlations than did the POMS. Univariate regressions based only on initial performance adequately predicted retest performance for the majority of measures. Age and education had a relatively minor influence. Practice effects and regression to the mean were common. These test–retest regression equations can be used to predict retest scores when there has been no known intervention. They can also be used to generate statistical statements regarding the significance of change in an individual's performance over a 12-to-16-week interval. (JINS, 2001, 7, 597–605.)

Type
Research Article
Copyright
© 2001 The International Neuropsychological Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)