Journal
QUALITY & QUANTITY
Volume 42, Issue 3, Pages 369-396Publisher
SPRINGER
DOI: 10.1007/s11135-006-9050-6
Keywords
interaction effects; structural equation models; indirect effects; non-linear constraints; mean structure; normality assumption
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Structural equation models with mean structure and non-linear constraints are the most frequent choice for estimating interaction effects when measurement errors are present. This article proposes eliminating the mean structure and all the constraints but one, which leads to a more easily handled model that is more robust to non-normality and more general as it can accommodate endogenous interactions and thus indirect effects. Our approach is compared to other approaches found in the literature with a Monte Carlo simulation and is found to be equally efficient under normality and less biased under non-normality. An empirical illustration is included.
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