Open Access. Powered by Scholars. Published by Universities.®
Social and Behavioral Sciences Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Social and Behavioral Sciences
A New Estimator Based On Auxiliary Information Through Quantitative Randomized Response Techniques, Nilgün Özgül, Hülya Çıngı
A New Estimator Based On Auxiliary Information Through Quantitative Randomized Response Techniques, Nilgün Özgül, Hülya Çıngı
Journal of Modern Applied Statistical Methods
An exponential-type estimator is developed for the population mean of the sensitive study variable based on various Randomized Response Techniques (RRT) using a non-sensitive auxiliary variable. The mean squared error (MSE) of the proposed estimator is derived for generalized RRT models. The proposed estimator is compared with competitors in a simulation study and an application. The proposed estimator is found to be more efficient using a non-sensitive auxiliary variable.
Effective Estimation Strategy Of Finite Population Variance Using Multi-Auxiliary Variables In Double Sampling, Reba Maji, G. N. Singh, Arnab Bandyopadhyay
Effective Estimation Strategy Of Finite Population Variance Using Multi-Auxiliary Variables In Double Sampling, Reba Maji, G. N. Singh, Arnab Bandyopadhyay
Journal of Modern Applied Statistical Methods
Estimation of population variance in two-phase (double) sampling is considered using information on multiple auxiliary variables. An unbiased estimator is proposed and its properties are studied under two different structures. The superiority of the suggested estimator over some contemporary estimators of population variance was established through empirical studies from a natural and an artificially generated dataset.