ESTIMATION OF POPULATION MEAN UNDER DIFFERENT STRATIFIED RANKED SET SAMPLING DESIGNS WITH SIMULATION STUDY APPLICATION TO BMI DATA

Abstract

In this article, we have compared the performance of ratio-type estimators in some stratified ranked set sampling methods. These sampling methods are stratified random sampling, stratified ranked set sampling, stratified double ranked set sampling and stratified median ranked set sampling. In these methods, the ratio type estimators using auxiliary variable information such as coefficient of variation and kurtosis are examined. We have used a real data set to see the performance of estimators. We use the data concerning body mass index (BMI) as a study variable and the age and the weight as auxiliary variables for 800 people in Turkey in 2014. We stratified the data set using gender. A simulation study is carried out to see performance of the proposed ratio type estimators in these stratified ranked set sampling designs. The performances of these estimators are compared in terms of mean squared error (MSE) and percent relative efficiency (PRE). The importance of this study is to compare these stratified sampling designs with those in the sampling literature by performing a detailed simulation using a real data set.