Improved estimation of population variance in stratified successive sampling using calibrated weights under non-response
M.K. Pandey,
G.N. Singh,
Tolga Zaman,
Aned Al Mutairi,
Manahil SidAhmed Mustafa
Affiliations
M.K. Pandey
Department of Mathematics & Computing, Indian Institute of Technology (Indian School of Mines), Dhanbad, 826 004, Jharkhand, India; Corresponding author.
G.N. Singh
Department of Mathematics & Computing, Indian Institute of Technology (Indian School of Mines), Dhanbad, 826 004, Jharkhand, India
Tolga Zaman
Faculty of Health Sciences, Gumushane University, Gumushane, Turkey
Aned Al Mutairi
Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
Manahil SidAhmed Mustafa
Department of Statistics, Faculty of Science, University of Tabuk, Tabuk, Saudi Arabia
This paper introduces a new method to estimate the population variance of a study variable in stratified successive sampling over two occasions, while accounting for random non-response. The method uses a logarithmic type estimator and leverages information from a highly positively correlated auxiliary variable. The paper also presents calibrated weights for the new estimator and examines its properties through numerical and simulation studies. The results indicate that the suggested estimator is more effective than the standard estimator for estimating the population variance.