Raykov Tenko, Marcoulides George A, Patelis Thanos
Michigan State University, East Lansing, MI, USA.
University of California at Santa Barbara, Santa Barbara, CA, USA.
Educ Psychol Meas. 2015 Aug;75(4):634-647. doi: 10.1177/0013164414548217. Epub 2014 Aug 27.
A critical discussion of the assumption of uncorrelated errors in classical psychometric theory and its applications is provided. It is pointed out that this assumption is essential for a number of fundamental results and underlies the concept of parallel tests, the Spearman-Brown's prophecy and the correction for attenuation formulas as well as the discrepancy between observed and true correlations, and the upper bound property of the reliability index with respect to validity. These relationships are shown not to hold if the errors of considered pairs of tests are correlated. The assumption of lack of error correlation is demonstrated not to be testable using standard covariance structure analysis for pairs of indivisible measures evaluating the same true score with identical error variances.
对经典心理测量理论中不相关误差假设及其应用进行了批判性讨论。指出该假设对于许多基本结果至关重要，并且是平行测验概念、斯皮尔曼 - 布朗预测公式、衰减校正公式以及观测相关性与真实相关性之间差异以及可靠性指数相对于效度的上限性质的基础。如果所考虑的测验对的误差是相关的，这些关系将不成立。对于评估具有相同误差方差的相同真分数的不可分割测量对，使用标准协方差结构分析表明，误差不相关的假设是不可检验的。
