What question did this study set out to answer?

This study aims to enhance the efficiency of estimators in survey sampling by introducing robust regression methods for addressing outliers and sensitive variables.

May 22, 2026Hacettepe Journal of Mathematics and StatisticsOpen Access

A robust calibration-based estimator in presence of non-sensitive and sensitive variables using moments in sample surveys

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This study aims to enhance the efficiency of estimators in survey sampling by introducing robust regression methods for addressing outliers and sensitive variables.
Developed robust regression approaches for calibrated exponential ratio-type estimators.
Utilized stratified random sampling to incorporate first three moments of auxiliary variables.
Conducted simulation studies with introduced outliers at specified rates (5%, 10%, 25%).
Robust estimators showed improved performance over existing methods, particularly in handling outliers and sensitive variables.
Enhanced accuracy in estimating the means for finite populations, indicating higher precision with sensitive data.
Successful reduction of bias in responses related to personal relationships and health issues.

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Implication

Randomized trial introduces robust estimators improving accuracy with sensitive data, suggesting better precision in survey sampling.

Cite This Study

Yadav et al. (2026) studied this question.

synapsesocial.com/papers/6a0ff43fd674f7c03778d716 https://doi.org/10.15672/hujms.1687321

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A robust calibration-based estimator in presence of non-sensitive and sensitive variables using moments in sample surveys

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Discussion

Implication

Cite This Study

A robust calibration-based estimator in presence of non-sensitive and sensitive variables using moments in sample surveys

Key Points

Discussion

Implication

Cite This Study

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