Calibration approach for non response adjustment under ranked set sampling

Naila Alam; Nida Khalil

Author(s)

Naila Alam Department of Statistics, Kinnaird College for Women, Lahore, Pakistan

Nida Khalil Department of Statistics, Kinnaird College for Women, Lahore, Pakistan

Abstract

Non-response poses a significant concern within survey sampling, occurring when individuals are either unavailable or unwilling to respond to survey questions. To address this issue, the application of non-response adjustment through auxiliary variables is widely employed to estimate missing data points. This study delves into the extensive possibilities presented by this approach, particularly focusing on calibration weighting. The study specifically investigates the challenge of non-response within the context of ranked set sampling (RSS). Within this study, we introduce two novel calibration estimators for population means. One estimator addresses scenarios of complete response, while the other pertains to cases of non-response under the ranked set sampling technique. To evaluate their performance, the Mean Square Error (MSE) and Bias expressions are derived. Furthermore, the performance of the proposed estimators is assessed through comprehensive simulation studies, encompassing both artificial and real-world datasets. For this purpose, the Mean Square Error and Bias for the ranked set samples of sizes 5, 8, 10, and 25, encompassing a total of 10,000 samples for each size category are calculated. Our findings reveal that the proposed calibration estimator, along with the imputation through calibration for non-response, consistently generates more efficient estimates compared to mean and median imputation techniques. This underscores the potential of the calibration approach in mitigating the impact of non-response, offering improved accuracy and robustness in survey sampling. .

Publication Details

Page(s) 301-314

DOI DOI not available

Published Journal: Pakistan Journal of Statistics, Volume: 40, Issue: 3, Year: 2024

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Keywords

mean square error, Rank set sampling, Non-Response, Calibration

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