A generalized class of estimators for sensitive variable in the presence of measurement error and non-response under stratified random sampling
Erum Zahid, Javid Shabbir, Osama Abdulaziz Alamri
Abstract
In survey sampling an investigator may be unable to get the complete and correct information at the same time. So non-response and measurement error occur simultaneously and consequently may effect the estimator. Considering this problem, a generalized class of estimators is proposed for estimating the finite population mean for sensitive variable in the presence of measurement error and non-response under stratified random sampling. We conducted a study based on real data set at Quaid-i-Azam University, Islamabad. Simulation and real life data sets are used to observe the performances of the estimators. Bias and MSE values are given for the comparison of estimators.
Topics & Concepts
EstimatorStratified samplingStatisticsSampling (signal processing)Population meanMathematicsClass (philosophy)Observational errorSimple random sampleVariable (mathematics)PopulationSet (abstract data type)Computer scienceArtificial intelligenceMathematical analysisComputer visionFilter (signal processing)DemographyProgramming languageSociologySurvey Sampling and Estimation Techniques