Mean estimation of sensitive variables under measurement errors and non-response

UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
Qi Zhang (Creator)
The University of North Carolina at Greensboro (UNCG )
Web Site:
Sat Gupta

Abstract: This study mainly consists of three important issues we face in survey sampling: social desirability bias, measurement errors, and non-response. In this dissertation, we study the mean estimation of a sensitive variable under measurement errors and non-response. We propose a generalized mean estimator, then discuss the bias and the mean square error (MSE) of this estimator and present the comparisons with other estimators under the measurement errors and non-response using optional RRT model (ORRT). We also study the performance of the proposed estimator under the same situations using stratified random sampling. Simulation studies are also conducted to verify the theoretical results. Both the theoretical and empirical results show that the generalized mean estimator is more efficient than the ordinary RRT estimator that does not utilize the auxiliary variable, and the ratio estimator which is one of the commonly used mean estimator.

Additional Information

Language: English
Date: 2020
Measurement Error, Non-response, RRT
Sampling (Statistics)
Estimation theory

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