Ratio-type estimator of the population mean in stratified sampling based on the calibration approach

Menakshi Pachori; Neha Garg

doi:https://doi.org/10.59170/stattrans-2024-014

Ratio-type estimator of the population mean in stratified sampling based on the calibration approach

Menakshi Pachori School of Sciences, Indira Gandhi National Open University, New Delhi-110068, India ORCID:https://orcid.org/0000-0001-5917-9648 , Neha Garg Corresponding author. School of Sciences, Indira Gandhi National Open University, New Delhi-110068, India ORCID:https://orcid.org/0000-0003-3123-1832 Statistics in Transition new series, vol. 25, 2024, 2, pages: 39-55 Published online: 5 June 2024 https://doi.org/10.59170/stattrans-2024-014 Citation: Pachori, M., Garg, N., 2024. Ratio-type estimator of the population mean in stratified sampling based on the calibration approach. Statistics in Transition new series, 25(2), pp. 39-55. https://doi.org/10.59170/stattrans-2024-014

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ABSTRACT

An improved ratio-type calibrated estimator was developed using the logarithmic mean in the calibration constraint for the stratified random sampling scheme. The proposed estimator was extended in the case of stratified double sampling and compared with the estimators given by Tracy et al. (2003) together its ratio-type estimators, as well as Nidhi et al. (2017) and Khare et al. (2022). A simulation study was also carried out on both a real and artificial dataset in order to evaluate the performance of the proposed estimator compared to the existing estimators.

KEYWORDS

auxiliary information, calibration estimation, stratified random sampling, stratified double sampling, ratio estimator.

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