An efficient class of estimators for finite population mean in the presence of non-response under ranked set sampling (RSS)

Abstract

In this study, we address the problem of estimating the finite population mean when the non-response occurs on the characteristics under study. We propose a class of Rao-regression type estimators when ranked set sampling (RSS) procedure is used to collect the data from non-response group only and from both, the response and non-response groups. The information provided on the auxiliary variable is used at both stages i.e., at designing stage and the estimation stage. Expressions for bias and mean square error of the estimators are obtained up to first order of approximation. A comprehensive simulation study is carried out to observe the performances of the estimators under non-response.

Some Optimal Classes of Estimators Based on Multi-Auxiliary Information

“…[19] investigated a novel class of regression cum ratio estimators of population mean based on RSS. Some comprehensive studies based on RSS were presented by [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34].…”

An Improvement in Estimating the Population Mean Based on Family of Estimators with Different Application Areas

“…),Anieting et al (2020);Ahmad et al (2022);Ahmadini et al (2022);Fatima et al (2022);Rehman and Shabbir (2022) andSharma et al (2022) recently proposed various type of estimators for the estimation of 𝑌 ̅ under both cases in the literature. Especially, there are also many proposed estimators using exponential function strategy in the literature under non-response scheme.…”