New improved calibration estimator based on two auxiliary variables in stratified two-phase sampling

Ozgul N.

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, cilt.91, sa.6, ss.1243-1256, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 91 Sayı: 6
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1080/00949655.2020.1844702
  • Dergi Adı: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Business Source Elite, Business Source Premier, CAB Abstracts, Communication Abstracts, Metadex, Veterinary Science Database, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1243-1256
  • Anahtar Kelimeler: Calibration estimation, stratified two-phase sampling, auxiliary information, regression estimation, Lagrange multiplier technique
  • Hacettepe Üniversitesi Adresli: Evet

Özet

This paper considers the problem of estimating the population mean of the study variable when auxiliary information is not available and proposes new calibration approach alternative to the recent existing calibration estimators for estimating population mean of the study variable using two auxiliary variables in stratified two-phase sampling. The theory of new calibration estimation is given and optimum weights are derived under two-phase sampling approach. A simulation study is carried out to performance of the proposed calibration estimator with other existing calibration estimators. The results demonstrate that the proposed calibration estimator is more efficient than other existing calibration estimators of the population mean in stratified two-phase sampling.