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Parametric estimation of person parameters in cognitive diagnosis models hinges on posterior probabilities that are sample-dependent. This study investigates the impact of sample dependency on model calibration and scoring, proposing a multiple imputation procedure to correct it. Simulation results highlight the superiority of the new method with small samples.