Estimation of Finite Population Mean Calibrated for Unit Nonresponse using Two-Ancillary Variables

Shilpa Yadav¹ , Pankaj Nagar² , Kartik Arya³

Section:Research Paper, Product Type: Journal-Paper
Vol.10 , Issue.6 , pp.31-38, Dec-2023

Online published on Dec 31, 2023

Copyright © Shilpa Yadav, Pankaj Nagar, Kartik Arya . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Nonresponse is a pervasive issue in survey research, and it occurs when individuals selected to participate in a survey fail to respond or refuse to participate. The phenomenon of nonresponse can introduce biases in survey estimates and impact the validity and generalizability of survey findings. Over the years, researchers and statisticians have extensively studied nonresponse and developed various techniques to address its implications, amongst which calibration estimators provide a robust and statistically sound approach for adjusting nonresponse in surveys. In the present work, the authors have tried to develop calibration estimators using information on two ancillary variables for adjusting unit nonresponse and obtain estimates of the finite population mean for simple random sampling technique along with its respective variance. The proposed estimator is evaluated using simulation study, taking into consideration, different nonresponse mechanisms and varying calibration weights that proves that the proposed estimator is better than the traditional Hansen Hurwitz and imputation estimators as well.

Key-Words / Index Term :
Calibration, nonresponse, chi-square distance function, ancillary variable, simulation

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