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测量与可靠性:统计思维考量

Measurement and reliability: statistical thinking considerations.

作者信息

Bartko J J

机构信息

NIMH, Bethesda, MD 20892.

出版信息

Schizophr Bull. 1991;17(3):483-9. doi: 10.1093/schbul/17.3.483.

Abstract

Reliability is defined as the degree to which multiple assessments of a subject agree (reproducibility). There is increasing awareness among researchers that the two most appropriate measures of reliability are the intraclass correlation coefficient and kappa. However, unacceptable statistical measures of reliability such as chi-square, percent agreement, product moment correlation, as well as any measure of association and Yule's Y still appear in the literature. There are costs associated with improper measurements, unreliable diagnostic systems, inappropriate statistics and measures of reliability, and poor quality research. Costs are incurred when misleading information directs resources and talents into nonproductive avenues of research. The consequences of unreliable measurements and diagnosis are illustrated with some studies of schizophrenia.

摘要

可靠性被定义为对一个对象进行多次评估时达成一致的程度(可重复性)。研究人员越来越意识到,可靠性的两种最合适的度量方法是组内相关系数和kappa系数。然而,诸如卡方检验、百分比一致性、积差相关以及任何关联度量和尤尔Y等不可接受的可靠性统计度量方法仍出现在文献中。不当测量、不可靠的诊断系统、不恰当的统计和可靠性度量方法以及质量不佳的研究都会带来成本。当误导性信息将资源和人才导向无成效的研究途径时,就会产生成本。一些关于精神分裂症的研究说明了不可靠测量和诊断的后果。

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