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人口统计学校正似乎会影响严重偏态认知测试的分类准确性。

Demographic corrections appear to compromise classification accuracy for severely skewed cognitive tests.

机构信息

Department of Psychology, University of Saskatchewan, Saskatoon, SK, Canada.

出版信息

J Clin Exp Neuropsychol. 2011 Apr;33(4):422-31. doi: 10.1080/13803395.2010.532114. Epub 2010 Dec 10.

Abstract

Demographic corrections for cognitive tests should improve classification accuracy by reducing age or education biases, but empirical support has been equivocal. Using a simulation procedure, we show that creating moderate or extreme skewness in cognitive tests compromises the classification accuracy of demographic corrections, findings that appear replicated within clinical data for the few neuropsychological test scores with an extreme degree of skew. For most neuropsychological tests, the dementia classification accuracy of raw and demographically corrected scores was equivalent. These findings suggest that the dementia classification accuracy of demographic corrections is robust to slight degrees of skew (i.e., skewness <1.5).

摘要

人口统计学校正可以通过减少年龄或教育的偏差来提高认知测试的分类准确性,但其实证支持一直存在争议。我们使用模拟程序表明,在认知测试中产生中度或极端偏态会影响人口统计学校正的分类准确性,这一发现似乎在具有极端偏态的少数神经心理学测试分数的临床数据中得到了复制。对于大多数神经心理学测试,原始和人口统计学校正分数的痴呆分类准确性是等效的。这些发现表明,人口统计学校正的痴呆分类准确性对轻微的偏态(即偏度<1.5)具有稳健性。

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