The Impact of Misspecifying the Within-Subject Covariance Structure in Multiwave Longitudinal Multilevel Models: A Monte Carlo Study
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This Monte Carlo study examined the impact of misspecifying the matrix in longitudinal data analysis under both the multilevel model and mixed model frameworks. Under the multilevel model approach, under-specification and generalmisspecification of the matrix usually resulted in overestimation of the variances of the random effects (e.g., 00, 11) and standard errors of the corresponding growth parameter estimates (e.g., SE0, SE1). Overestimates of the standard errors led to lower statistical power in tests of the growth parameters. An unstructured matrix under the mixed model framework generally led to underestimates of standard errors of the growth parameter estimates. Underestimates of the standard errors led to inflation of me type I error rate in tests of the growth parameters. Implications of the compensatory relationship between the random effects of the growth parameters and the longitudinal error structure for model specification were discussed. Copyright 2007, Lawrence Erlbaum Associates, Inc.
