Calibration-Based Mean Estimators under Stratified Median Ranked Set Sampling

Usman Shahzad (), Ishfaq Ahmad, Fatimah Alshahrani, Ibrahim M. Almanjahie and Soofia Iftikhar
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Usman Shahzad: Department of Mathematics and Statistics, International Islamic University, Islamabad 44000, Pakistan
Ishfaq Ahmad: Department of Mathematics and Statistics, International Islamic University, Islamabad 44000, Pakistan
Fatimah Alshahrani: Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
Ibrahim M. Almanjahie: Department of Mathematics, College of Science, King Khalid University, Abha 62223, Saudi Arabia
Soofia Iftikhar: Department of Statistics, Shaheed Benazir Bhutto Women University, Peshawar 25120, Pakistan

Mathematics, 2023, vol. 11, issue 8, 1-21

Abstract: Using auxiliary information, the calibration approach modifies the original design weights to enhance the mean estimates. This paper initially proposes two families of estimators based on an adaptation of the estimators presented by recent researchers, and then, it presents a new family of calibration estimators with the set of some calibration constraints under stratified median ranked set sampling (MRSS). The result has also been implemented to the situation of two-stage stratified median ranked set sampling (MRSS). To best of our knowledge, we are presenting for the first time calibration-based mean estimators under stratified MRSS, so the performance evaluation is made between adapted and proposed estimators on behalf of the simulation study with real and artificial datasets. For real-world data or applications, we use information on the body mass index (BMI) of 800 people in Turkey in 2014 as a research variable and age as an auxiliary variable.

Keywords: median ranked set sampling; two-stage median ranked set sampling; auxiliary information; calibration-type estimators (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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