Unbiased ratio estimators of the mean in stratified ranked set sampling

Abstract

Stratified ranked set sampling (StRSS) combines the advantages of stratification and ranked set sampling (RSS). In this paper, we propose several unbiased ratio type estimators using StRSS, when population mean of the auxiliary variable is known. The variances of the proposed unbiased ratio-type estimators are obtained to first degree of approximation. In simulation study the proposed estimators are more efficient as compared to other competitor estimators using Percentage Relative Efficiency (PRE), Percentage Relative Bias (PRB) and Percentage Relative Root Mean Square Error (PRRMSE).