Developing calibration estimators for population mean using robust measures of dispersion under stratified random sampling


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Statistics in Transition New Series

Polish Statistical Association

Central Statistical Office of Poland

Subject: Economics, Statistics & Probability


ISSN: 1234-7655
eISSN: 2450-0291





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VOLUME 22 , ISSUE 2 (June 2021) > List of articles

Developing calibration estimators for population mean using robust measures of dispersion under stratified random sampling

Ahmed Audu / Rajesh Singh / Supriya Khare *

Keywords : calibration, outliers, percentage relative efficiency (PRE), stratified sampling

Citation Information : Statistics in Transition New Series. Volume 22, Issue 2, Pages 125-142, DOI:

License : (CC BY-NC-ND 4.0)

Received Date : 30-December-2019 / Accepted: 22-September-2020 / Published Online: 13-June-2021



In this paper, two modified, design-based calibration ratio-type estimators are presented. The suggested estimators were developed under stratified random sampling using information on an auxiliary variable in the form of robust statistical measures, including Gini’s mean difference, Downton’s method and probability weighted moments. The properties (biases and MSEs) of the proposed estimators are studied up to the terms of firstorder approximation by means of Taylor’s Series approximation. The theoretical results were supported by a simulation study conducted on four bivariate populations and generated using normal, chi-square, exponential and gamma populations. The results of the study indicate that the proposed calibration scheme is more precise than any of the others considered in this paper.

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