On the "optimal" size for normative samples in neuropsychology: Capturing the uncertainty when normative data are used to quantify the standing of a neuropsychological test score

Crawford, John R. and Garthwaite, Paul H. (2008). On the "optimal" size for normative samples in neuropsychology: Capturing the uncertainty when normative data are used to quantify the standing of a neuropsychological test score. Child Neuropsychology, 14(2) pp. 99–117.

DOI: https://doi.org/10.1080/09297040801894709

Abstract

Bridges and Holler (2007) have provided a useful reminder that normative data are fallible. Unfortunately, however, their paper misleads neuropsychologists as to the nature and extent of the problem. We show that the uncertainty attached to the estimated z score and percentile rank of a given raw score is much larger than they report and that it varies as a function of the extremity of the raw score. Methods for quantifying the uncertainty associated with normative data are described and used to illustrate the issues involved. A computer program is provided that, on entry of a normative sample mean, standard deviation, and sample size, provides point and interval estimates of percentiles and z scores for raw scores referred to these normative data. The methods and program provide neuropsychologists with a means of evaluating the adequacy of existing norms and will be useful for those planning normative studies.

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