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Embedded Performance Validity Measures with Postdeployment Veterans: Cross-Validation and Efficiency with Multiple Measures

机译:具有部署后退伍军人的嵌入式性能有效性度量:具有多个度量的交叉验证和效率

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摘要

Embedded validity measures support comprehensive assessment of performance validity. The purpose of this study was to evaluate the accuracy of individual embedded measures and to reduce them to the most efficient combination. The sample included 212 postdeployment veterans (average age = 35 years, average education = 14 years). Thirty embedded measures were initially identified as predictors of Green's Word Memory Test (WMT) and were derived from the California Verbal Learning Test-Second Edition (CVLT-II), Conners' Continuous Performance Test-Second Edition (CPT-II), Trail Making Test, Stroop, Wisconsin Card Sorting Test-64, the Wechsler Adult Intelligence Scale-Third Edition Letter-Number Sequencing, Rey Complex Figure Test (RCFT), Brief Visuospatial Memory Test-Revised, and the Finger Tapping Test. Eight nonoverlapping measures with the highest area-under-the-curve (AUC) values were retained for entry into a logistic regression analysis. Embedded measure accuracy was also compared to cutoffs
机译:嵌入式有效性度量支持对绩效有效性进行全面评估。这项研究的目的是评估单个嵌入式度量的准确性,并将其减少到最有效的组合。该样本包括212名部署后的退伍军人(平均年龄= 35岁,平均受教育程度= 14岁)。最初确定了30种嵌入式测度是格林的单词记忆测试(WMT)的预测指标,并源自加利福尼亚语言学习测验第二版(CVLT-II),康纳斯的持续性能测验第二版(CPT-II),跟踪制作测试,Stroop,威斯康星卡片分类测试64,韦氏成人智力量表(第三版)字母数字排序,雷伊复杂图形测试(RCFT),简短视觉空间记忆测试(修订版)和手指敲击测试。保留了具有最大曲线下面积(AUC)值的八个非重叠度量,以用于进行逻辑回归分析。嵌入式测量的准确性也与临界值进行了比较

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