Effects of Misspecifying the First-Level Error Structure in Two-Level Models of Change

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Abstract
Computer simulation methods were used to examine the sensitivity of model fit criteria to misspecification of the first-level error structure in two-level models of change, and then to examine the impact of misspecification on estimates of the variance parameters, estimates of the fixed effects, and tests of the fixed effects. Fit criteria frequently failed to identify the correct model when series lengths were short. Misspecification led to substantially biased estimates of variance parameters. The estimates of the fixed effects, however, remained unbiased for most conditions, and the tests of fixed effects were robust to misspecification for most conditions. The problems in the fixed effects occurred when nonlinear growth trajectories were coupled with data that were unequally spaced by different amounts for different individuals.

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