A Novel Generalized Chain Regression-Cum Ratio Estimator for Handling Non-response in Two-Phase Sampling

Rather K. U. I., Koçyiğit E. G.

QUALITY & QUANTITY, cilt.59, sa.3, ss.1-19, 2025 (Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 59 Sayı: 3
  • Basım Tarihi: 2025
  • Dergi Adı: QUALITY & QUANTITY
  • Derginin Tarandığı İndeksler: Scopus, International Bibliography of Social Sciences, ABI/INFORM, Index Islamicus, Political Science Complete, Psycinfo, Social services abstracts, Sociological abstracts, Worldwide Political Science Abstracts
  • Sayfa Sayıları: ss.1-19
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

We introduce a novel generalized chain regression-cum-chain ratio estimator for estimating population means, leveraging two auxiliary variables within a robust two-phase sampling design. The proposed estimator leverages two auxiliary variables within a robust two-phase sampling scheme. In particular, it employs an innovative sub-sampling technique aimed at addressing and mitigating non-response issues, which are common challenges in survey sampling. Our study considers three distinct scenarios: One in which non-response occurs in the study variable while both auxiliary variables are fully observed; another where non-response may occur in either one or both auxiliary variables; and a third where non-response is present in one auxiliary variable while the other remains fully responsive. For each scenario, we derive explicit expressions for bias and mean squared error, facilitating comprehensive comparisons with the conventional unbiased estimator and other established methods. To further validate the performance of our estimator, we conduct extensive simulation studies alongside empirical analyses. The findings suggest that our approach provides improved accuracy and efficiency, making it a valuable tool for enhancing the reliability of population mean estimates in practical applications.