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使用似然比通过性能效度测量来检测无效表现。

Using likelihood ratios to detect invalid performance with performance validity measures.

作者信息

Meyers John E, Miller Ronald M, Thompson Lisa M, Scalese Adam M, Allred Bonnie C, Rupp Zachary W, Dupaix Zacharias P, Junghyun Lee Amy

机构信息

Meyers Neuropsychological Services, Mililani, HI, USA.

出版信息

Arch Clin Neuropsychol. 2014 May;29(3):224-35. doi: 10.1093/arclin/acu001. Epub 2014 Feb 4.

Abstract

Larrabee (2008) applied chained likelihood ratios to selected performance validity measures (PVMs) to identify non-valid performances on neuropsychological tests. He presented a method of combining different PVMs with different sensitivities and specificities into an overall probability of non-validity. We applied his methodology to a set of 11 PVMs using a sample of 255 subjects. The results of the study show that in various combinations of two or three PVMs, a high reliability of invalidity can be determined using the chained likelihood ratio method. This study advances the ability of clinicians to chain various PVMs together and calculate the probability that a set of data is invalid.

摘要

拉腊比(2008年)将连锁似然比应用于选定的效标效度测量指标(PVMs),以识别神经心理测试中的无效表现。他提出了一种方法,将具有不同敏感性和特异性的不同PVMs组合成无效的总体概率。我们使用255名受试者的样本,将他的方法应用于一组11个PVMs。研究结果表明,在两个或三个PVMs的各种组合中,使用连锁似然比方法可以确定较高的无效可靠性。这项研究提高了临床医生将各种PVMs联系在一起并计算一组数据无效概率的能力。

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