Graham J W, Collins N L
Multivariate Behav Res. 1991 Oct 1;26(4):607-29. doi: 10.1207/s15327906mbr2604_3.
Confirmatory factor analysis of multitrait-multimethod (MTMM) data has proven to be a useful tool for assessing convergent and discriminant validity. However, researchers have not made full use of the results of MTMM analyses in examining the relationship between MTMM factors and variables outside the MTMM. Often, researchers simply average the various measures of each trait. Alternatively, they estimate LISREL MTMM models, but estimate only relationships between MTMM traits and the outside variables. In the present article, we show that these two approaches to analyzing data outside the MTMM produce equally highly biased parameter estimates when the actual correlations between MTMM method factors and the outside variables are substantial. An algebraic explanation and a simulated data illustration are given for the bias due to misspecification. Also, the problem is illustrated with a brief empirical example. Implications for applied research are discussed.
多特质-多方法（MTMM）数据的验证性因素分析已被证明是评估聚合效度和区分效度的有用工具。然而，研究人员在检验MTMM因素与MTMM之外的变量之间的关系时，尚未充分利用MTMM分析的结果。通常，研究人员只是简单地对每个特质的各种测量值求平均值。或者，他们估计LISREL MTMM模型，但只估计MTMM特质与外部变量之间的关系。在本文中，我们表明，当MTMM方法因素与外部变量之间的实际相关性很大时，这两种分析MTMM之外数据的方法会产生同样高度有偏差的参数估计。针对因模型设定错误导致的偏差给出了代数解释和模拟数据说明。此外，还通过一个简短的实证例子说明了该问题。讨论了对应用研究的启示。
