Estimation of population mean under different stratified ranked set sampling designs with simulation study application to BMI data

Year 2020, Volume: 69 Issue: 1, 560 - 575, 30.06.2020

Arzu Ece Çetin , Nursel Koyuncu

https://doi.org/10.31801/cfsuasmas.649909

Cited By: 3

Abstract

In this article, we have compared the performance 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 that, a detail simulation study is done using a real data set and compare these stratified sampling designs in a study in the sampling literature.

Keywords

Stratified sampling, Stratified ranked set sampling, Median ranked set sampling, Ratio-type estimators, Auxiliary variables, Mean squared error, Population mean, Efficiency, Body mass index

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