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It is important to consider if this recommendation is valid in other empirical examples, and if it translates to epidemiological studies. This situation may also arise in clinical trials when interactions occur between treatment effects and covariates, or when adjustment is needed for prognostic factors that are unbalanced between groups. Thus the random-effects framework needs to accommodate these covariates during modeling in order to estimate factor-outcome associations after adjusting for other factors.