无回答与计量误差叠加时总体方差的校准估计OA北大核心CHSSCDCSSCICSTPCD

Non-sampling error is a kind of systematic error that may exist in probability sampling,non-probability sampling and overall survey,and will have an important impact on the quality of statistical data and estimated results.At present,there are insufficient researches on the estimation of finite population parameters from the perspective of non-sampling error,and few re-searches on the estimation of population variance when multiple non-sampling errors are superimposed.This paper is based on the calibration estimation method to the estimation of finite population variance in stratified random sampling when the two kinds of non-sampling errors exist simultaneously,and then proposes an improved population variance calibration estimator for the case of non-response and measurement error superposition.Finally,on this basis,the paper investigates the statistical properties of the proposed calibration estimator,and deduces the first-order approximate mathematical expressions of its deviation and mean square error.Both the simulation studies and real data results show that the proposed calibration estimators are always more effi-cient than Singh's standard estimators.