Browsing by Author "Manoj Kumar Chaudhary"

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An Efficient Use of Calibration Technique for Estimating the Stratified Population Mean in the Presence of Measurement Error and Non-Response
(Springer Nature, 2025) Manoj Kumar Chaudhary; Shilpa Minz
The calibration techniques are used in survey sampling to get a precise estimate of the population parameter. In the present paper, we propose an efficient calibrated estimator of the stratified population mean using calibration technique in the simultaneous presence of measurement error and non-response, which has received limited attention in the existing literature. The information on a single auxiliary variable is utilized to envisage the calibrated estimator. The properties of the proposed calibrated estimator have been studied. The Taylor linearization technique has been used to derive the expression for the mean square error of the proposed calibrated estimator. An empirical study along with simulation analysis has also been accomplished to validate the efficiency of the proposed calibrated estimator. The study reveals that the proposed calibrated estimator outperforms over the estimators suggested by Hansen and Hurwitz (J Am Stat Assoc 41(236):517–529, 1946), Azeem and Hanif (Commun Stat-Theory Methods 46(4):1679–1693, 2017), Zahid and Shabbir (PLUS One 13(2):1–12, 2018) and Singh et al. (Rev Invest Oper 41(1):125–137, 2020). This work has contributed to extending calibration methodology to construct an estimator that performs effectively in the joint presence of measurement error and non-response. © Grace Scientific Publishing 2025.
Treating the problem of non-response in stratified random sampling under calibration approach
(Taylor and Francis Ltd., 2025) Manoj Kumar Chaudhary; Basant Kumar Ray
In the present study, we suggested a chi-square-type distance function that works well for non-response situations and we have derived a new calibration-based estimator using such a kind of distance function, which is used to estimate the mean of a stratified population. The proposed estimator is derived through the implementation of a reweighting technique referred to as the calibration approach, aimed at improving upon Hansen and Hurwitz’s (1946) estimator. Typically, in situations where some units do not respond, researchers adjust the stratum weights to obtain an estimator for the mean of a stratified population using the calibration approach. In this study, the weights given to the responding units in the sample and the units in the sub-sample taken from the non-responding sample were calibrated to derive the calibration estimator. We assume that the unit non-response problem impacts both study and auxiliary variables. To examine the performance of the proposed calibration estimator in scenarios involving non-response, we have carried out empirical studies. © 2024 Taylor & Francis Group, LLC.