NOTES ON THE ESTIMATORS PROPERTIES IN CASE OF IMPUTED DATA SETS (Uwagi na temat wlasnosci estymatorow wyznaczanych na bazie niepelnych danych)
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In current surveys practice the most common method for handling non-response item is simple imputation. The simple imputation methods are the prediction methods for missing data. The imputed values are treated as if they were observed. This results in under or overestimation of the estimator variance, especially if the missing data mechanism is non-random. Simple imputation is inappropriate when the goal is to construct test statistics and confidence of intervals. The paper shows examples of the impact of imputation on the estimates properties. One solution is to use multiple imputation methods that take into account the so-called imputation error.
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