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Reliable Change Formula Query: Temkin et al. reply

Published online by Cambridge University Press:  01 March 2000

NANCY R. TEMKIN
Affiliation:
Department of Neurological Surgery, University of Washington, Seattle, Washington Department of Biostatistics, University of Washington, Seattle, Washington
ROBERT K. HEATON
Affiliation:
Department of Psychiatry, University of California, San Diego, La Jolla, California
IGOR GRANT
Affiliation:
Department of Psychiatry, University of California, San Diego, La Jolla, California VA San Diego Healthcare System, San Diego, California
SUREYYA S. DIKMEN
Affiliation:
Department of Neurological Surgery, University of Washington, Seattle, Washington Department of Rehabilitation Medicine, University of Washington, Seattle, Washington Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington
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Abstract

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Hinton-Bayre (2000) raises a point that may occur to many readers who are familiar with the Reliable Change Index (RCI). In our previous paper comparing four models for detecting significant change in neuropsychological performance (Temkin et al., 1999), we used a formula for calculating Sdiff, the measure of variability for the test–retest difference, that differs from the one Hinton-Bayre has seen employed in other studies of the RCI. In fact, there are two ways of calculating Sdiff—a direct method and an approximate method. As stated by Jacobson and Truax (1991, p. 14), the direct method is to compute “the standard error of the difference between the two test scores” or equivalently [begin square root](s12 + s22 − 2s1 s2 rxx′)[end square root] where si is the standard deviation at time i and rxx′ is the test–retest correlation or reliability coefficient. Jacobson and Truax also provide a formula for the approximation of Sdiff when one does not have access to retest data on the population of interest, but does have a test–retest reliability coefficient and an estimate of the cross-sectional standard deviation, i.e., the standard deviation at a single point in time. This approximation assumes that the standard deviations at Time 1 and Time 2 are equal, which may be close to true in many cases. Since we had the longitudinal data to directly calculate the standard error of the difference between scores at Time 1 and Time 2, we used the direct method. Which method is preferable? When the needed data are available, it is the one we used.

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LETTER TO THE EDITOR
Copyright
© 2000 The International Neuropsychological Society
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Reliable Change Formula Query: Temkin et al. reply
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