Sample surveys are taken with the assumption that all the sampled elements will respond. However, this is not always the case. Sometimes missing values occur in the survey data due to some reasons. In cases of such missing values, any inference from the data will survey from a non-response error. Therefore, the researcher needed to put all measures in place to prevent the occurrence of the missing values in the data. However, this is not easily achieved. The non-response may occur even after all measures to prevent it have been put in place. Therefore, there is a need to correct the error if it so happens. The current paper seeks to improve the Hansel and Hurwitz (1946) estimator using poststratification. The proposed estimator can be as well be improved. Therefore, the current study proposes an improvement of the Hansel and Hurwitz (1946) estimator using the median of the auxiliary variable. The efficiency of the new proposed estimator is checked using the confidence interval length. Which is the on-coverage property of the estimator. On to the recommendation a band with that will reduce the variance in case of high non-response rate is thus suggested for further studies. Beside we suggest further studies on how both variances and bias will be minimized without any of them being minimized in expense of the other.
| Published in | American Journal of Theoretical and Applied Statistics (Volume 11, Issue 3) |
| DOI | 10.11648/j.ajtas.20221103.12 |
| Page(s) | 89-93 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2022. Published by Science Publishing Group |
Confidence Interval, Variance, No-Response, Mean
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APA Style
Charles Wanyingi Nderitu, Herbert Imboga, Samuel Mwangi Gathuka. (2022). On the Coverage Properties of the Ratio Based Estimator in Presence of Non Response Error. American Journal of Theoretical and Applied Statistics, 11(3), 89-93. https://doi.org/10.11648/j.ajtas.20221103.12
ACS Style
Charles Wanyingi Nderitu; Herbert Imboga; Samuel Mwangi Gathuka. On the Coverage Properties of the Ratio Based Estimator in Presence of Non Response Error. Am. J. Theor. Appl. Stat. 2022, 11(3), 89-93. doi: 10.11648/j.ajtas.20221103.12
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Download@article{10.11648/j.ajtas.20221103.12,
author = {Charles Wanyingi Nderitu and Herbert Imboga and Samuel Mwangi Gathuka},
title = {On the Coverage Properties of the Ratio Based Estimator in Presence of Non Response Error},
journal = {American Journal of Theoretical and Applied Statistics},
volume = {11},
number = {3},
pages = {89-93},
doi = {10.11648/j.ajtas.20221103.12},
url = {https://doi.org/10.11648/j.ajtas.20221103.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20221103.12},
abstract = {Sample surveys are taken with the assumption that all the sampled elements will respond. However, this is not always the case. Sometimes missing values occur in the survey data due to some reasons. In cases of such missing values, any inference from the data will survey from a non-response error. Therefore, the researcher needed to put all measures in place to prevent the occurrence of the missing values in the data. However, this is not easily achieved. The non-response may occur even after all measures to prevent it have been put in place. Therefore, there is a need to correct the error if it so happens. The current paper seeks to improve the Hansel and Hurwitz (1946) estimator using poststratification. The proposed estimator can be as well be improved. Therefore, the current study proposes an improvement of the Hansel and Hurwitz (1946) estimator using the median of the auxiliary variable. The efficiency of the new proposed estimator is checked using the confidence interval length. Which is the on-coverage property of the estimator. On to the recommendation a band with that will reduce the variance in case of high non-response rate is thus suggested for further studies. Beside we suggest further studies on how both variances and bias will be minimized without any of them being minimized in expense of the other.},
year = {2022}
}
TY - JOUR T1 - On the Coverage Properties of the Ratio Based Estimator in Presence of Non Response Error AU - Charles Wanyingi Nderitu AU - Herbert Imboga AU - Samuel Mwangi Gathuka Y1 - 2022/05/19 PY - 2022 N1 - https://doi.org/10.11648/j.ajtas.20221103.12 DO - 10.11648/j.ajtas.20221103.12 T2 - American Journal of Theoretical and Applied Statistics JF - American Journal of Theoretical and Applied Statistics JO - American Journal of Theoretical and Applied Statistics SP - 89 EP - 93 PB - Science Publishing Group SN - 2326-9006 UR - https://doi.org/10.11648/j.ajtas.20221103.12 AB - Sample surveys are taken with the assumption that all the sampled elements will respond. However, this is not always the case. Sometimes missing values occur in the survey data due to some reasons. In cases of such missing values, any inference from the data will survey from a non-response error. Therefore, the researcher needed to put all measures in place to prevent the occurrence of the missing values in the data. However, this is not easily achieved. The non-response may occur even after all measures to prevent it have been put in place. Therefore, there is a need to correct the error if it so happens. The current paper seeks to improve the Hansel and Hurwitz (1946) estimator using poststratification. The proposed estimator can be as well be improved. Therefore, the current study proposes an improvement of the Hansel and Hurwitz (1946) estimator using the median of the auxiliary variable. The efficiency of the new proposed estimator is checked using the confidence interval length. Which is the on-coverage property of the estimator. On to the recommendation a band with that will reduce the variance in case of high non-response rate is thus suggested for further studies. Beside we suggest further studies on how both variances and bias will be minimized without any of them being minimized in expense of the other. VL - 11 IS - 3 ER -
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