Evaluation of Two Methods for Modeling Measurement Errors When Testing Interaction Effects With Observed Composite Scores

被引:26
作者
Hsiao, Yu-Yu [1 ]
Kwok, Oi-Man [1 ]
Lai, Mark H. C. [2 ]
机构
[1] Texas A&M Univ, College Stn, TX USA
[2] Univ Cincinnati, Cincinnati, OH USA
关键词
reliability; composite score; structural equation modeling; latent interaction effect; STRUCTURAL EQUATION MODELS; MAXIMUM-LIKELIHOOD-ESTIMATION; LATENT VARIABLE INTERACTIONS; MONTE-CARLO; RELIABILITY; STRATEGIES;
D O I
10.1177/0013164416679877
中图分类号
G44 [教育心理学];
学科分类号
0402 ; 040202 ;
摘要
Path models with observed composites based on multiple items (e.g., mean or sum score of the items) are commonly used to test interaction effects. Under this practice, researchers generally assume that the observed composites are measured without errors. In this study, we reviewed and evaluated two alternative methods within the structural equation modeling (SEM) framework, namely, the reliability-adjusted product indicator (RAPI) method and the latent moderated structural equations (LMS) method, which can both flexibly take into account measurement errors. Results showed that both these methods generally produced unbiased estimates of the interaction effects. On the other hand, the path modelwithout considering measurement errorsled to substantial bias and a low confidence interval coverage rate of nonzero interaction effects. Other findings and implications for future studies are discussed.
引用
收藏
页码:181 / 202
页数:22
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