Raykov Tenko, Menold Natalja, Marcoulides George A
Michigan State University, East Lansing, MI, USA.
Leibniz Institute for the Social Sciences, Mannheim, Germany.
Educ Psychol Meas. 2018 Oct;78(5):905-917. doi: 10.1177/0013164417698017. Epub 2017 Mar 26.
Validity coefficients for multicomponent measuring instruments are known to be affected by measurement error that attenuates them, affects associated standard errors, and influences results of statistical tests with respect to population parameter values. To account for measurement error, a latent variable modeling approach is discussed that allows point and interval estimation of the relationship of an underlying latent factor to a criterion variable in a setting that is more general than the commonly considered homogeneous psychometric test case. The method is particularly helpful in validity studies for scales with a second-order factorial structure, by allowing evaluation of the relationship between the second-order factor and a criterion variable. The procedure is similarly useful in studies of discriminant, convergent, concurrent, and predictive validity of measuring instruments with complex latent structure, and is readily applicable when measuring interrelated traits that share a common variance source. The outlined approach is illustrated using data from an authoritarianism study.
已知多成分测量工具的效度系数会受到测量误差的影响，测量误差会削弱效度系数，影响相关的标准误差，并影响关于总体参数值的统计检验结果。为了考虑测量误差，本文讨论了一种潜在变量建模方法，该方法允许在比通常考虑的同质心理测量测试案例更一般的环境中，对潜在因素与标准变量之间的关系进行点估计和区间估计。该方法在具有二阶因子结构的量表的效度研究中特别有用，它允许评估二阶因子与标准变量之间的关系。该程序在具有复杂潜在结构的测量工具的判别效度、收敛效度、同时效度和预测效度研究中同样有用，并且在测量具有共同方差源的相关特质时很容易应用。本文使用来自一项威权主义研究的数据说明了所概述的方法。
