Population Performance of SEM Parceling Strategies Under Measurement and Structural Model Misspecification

Previous research has suggested that the use of item parcels in structural equation modeling can lead to biased structural coefficient estimates and low power to detect model misspecification. The present article describes the population performance of items, parcels, and scales under a range of model misspecifications, examining structural path coefficient accuracy, power, and population fit indices. Results revealed that, under measurement model misspecification, any parceling scheme typically results in more accurate structural parameters, but less power to detect the misspecification. When the structural model is misspecified, parcels do not affect parameter accuracy, but they do substantially elevate power to detect the misspecification. Under particular, known measurement model misspecifications, a parceling scheme can be chosen to produce the most accurate estimates. The root mean square error of approximation and the standardized root mean square residual are more sensitive to measurement model misspecification in parceled models than the likelihood ratio test statistic. (PsycINFO Database Record