Joint Parameter Estimation in Measurement Errors and Non-Response for Sensitive Variables
DOI:
https://doi.org/10.64060/JASR.v1.i2.1Abstract
In this paper, joint parameter estimation for mean and variance was considered in the presence of measurement errors and non-response for the Sensitive variable using auxiliary information. The properties of the suggested estimator(s) have been studied. Expressions for bias and mean square error up to first order of approximation are derived, and the theoretical characteristics of the suggested estimators are scrutinised. A numerical study is carried out to observe the performance of the proposed estimators. The scope of this work is to create better estimators that can effectively manage both kinds of mistakes at the same time, especially in randomised response settings where biasing sensitive data is common. Applications to actual data and simulation studies are used to evaluate the estimators' effectiveness. When both measurement error and non-response are present, the results show that the suggested estimators outperform the traditional estimators.
Downloads
References
Azeem, M., & Hanif, M. (2016). Joint influence of measurement error and non-response on estimation of population mean. Communication in Statistics- Theory and Methods, 46(4), 1679–1693. https://doi.org/10.1080/03610926.2015.1026992
Azeem, M., Salahuddin, N., Hussain, S., Ijaz, M., & Salam, A. (2024). An efficient estimator of population variance of a sensitive variable with a new randomized response technique. Heliyon, 10(5), e27488. https://doi.org/10.1016/j.heliyon.2024.e27488
Bound, J., Brown, C., & Mathiowetz, N. (2001). Measurement error in survey data. In Handbook of econ-ometrics (pp. 3705–3843). https://doi.org/10.1016/s1573-4412(01)05012-7
Choudhary, M., Kour, S. P., Kumar, S., Bouza, C. N., & Santiago, A. (2023). Using ORRT Models for Mean Estimation under Nonresponse and Measurement Errors in Stratified Successive Sampling. Journal of Probability and Statistics, 2023, 1–17. https://doi.org/10.1155/2023/1340068
Cochran, W. G. (1968). Errors of measurement in statistics. Technometrics, 10(4), 637–666. https://doi.org/10.1080/00401706.1968.10490621 Fuller, W. A. (1995). Estimation in the pres-ence of measurement error. International Statistical Review, 63(2), 121–141.
Hansen, M. H., & Hurwitz, W. N. (1946). The problem of Non-Response in sample surveys. Journal of the American Statistical Association, 41(236), 517–529. https://doi.org/10.1080/01621459.1946.10501894
Hausman, J. (2001). Mismeasured Variables in Econometric Analysis: Problems from the Right and Prob-lems from the Left. The Journal of Economic Perspectives, 15(4), 57–67. https://doi.org/10.1257/jep.15.4.57
Khalil, S., Gupta, S., & Hanif, M. (2018). Estimation of finite population mean in stratified sampling using scrambled responses in the presence of measurement errors. Communication in Statistics- Theory and Methods, 48(6), 1553–1561. https://doi.org/10.1080/03610926.2018.1435817
Kreuter, F., Olson, K., Wagner, J., Yan, T., Ezzati-Rice, T. M., Casas-Cordero, C., Lemay, M., Pey-tchev, A., Groves, R. M., & Raghunathan, T. E. (2009). Using Proxy Measures and Other Corre-lates of Survey Outcomes to Adjust for Non-Response: Examples from Multiple Surveys. Journal of the Royal Statistical Society Series a (Statistics in Society), 173(2), 389–407. https://doi.org/10.1111/j.1467-985x.2009.00621.x
Kumar, S. (2016). Improved estimation of population mean in presence of non response and measurement error. Journal of Statistical Theory and Practice, 10(4), 707–720. https://doi.org/10.1080/15598608.2016.1216488
Kumar, S., Bhogal, S., Nataraja, N. S., & Viswanathaiah, M. (2015). Estimation of population mean in the presence of Non-Response and measurement error. Revista Colombiana De Estadística, 38(1), 145–161. https://doi.org/10.15446/rce.v38n1.48807
Manisha, & Singh, R. K. (2002). Role of regression estimator involving measurement errors. Brazilian Journal of Probability and Statistics, 16, 39–46.
Measurement errors in surveys. (2004). In Wiley series in probability and statistics. https://doi.org/10.1002/9781118150382
Meijer, E., & Wansbeek, T. (2000). Measurement error in a single regressor. Economics Letters, 69(3), 277–284. https://doi.org/10.1016/s0165-1765(00)00328-1
Okafor, F. C., & Lee, H. (2000). Double sampling for ratio and regression estimation with subsampling the nonrespondents. Survey Methodology, 26(2), 183–188. https://www150.statcan.gc.ca/n1/pub/12-001-x/2000002/article/5538-eng.pdf
Rosner, B. (2015). Fundamentals of Bio statistics. Cengage Learning.
Saleem, I., Sanaullah, A., Al-Essa, L. A., Bashir, S., & Mutairi, A. A. (2023). Efficient estimation of population variance of a sensitive variable using a new scrambling response model. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-45427-2
Shalabh. (1997). Ratio method of estimation in the presence of measurement errors. Journal of the Indian Society of Agricultural Statistics, 52, 150–155.
Sharma, P., & Singh, R. (2013). A generalized class of estimator for population variance in presence of measurement error. Journal of Modern Applied Statistical Methods, 12(2), 231–241. https://doi.org/10.22237/jmasm/1383279120 .
Shukla, D., Pathak, S., & Thakur, N. (2012). An estimator for mean estimation in presence of measure-ment error. Research and Reviews: A Journal of Statistics, 1(1), 1–8.
Singh, H. P., & Karpe, N. (2009). On the estimation of ratio and product of two populations means using supplementary information in presence of measurement errors. Rivista di Statistica Ufficiale, 69(1), 27–47.
Singh, H. P., & Kumar, S. (2008). A REGRESSION APPROACH TO THE ESTIMATION OF THE FINITE POPULATION MEAN IN THE PRESENCE OF NON‐RESPONSE. Australian & New Zealand Journal of Statistics, 50(4), 395–408. https://doi.org/10.1111/j.1467-842x.2008.00525.x
Singh, R. S., & Sharma, P. (2015). Method of estimation in the presence of non-response and measure-ment errors simultaneously. Journal of Modern Applied Statistical Methods, 14(1), Article 12. https://doi.org/10.22237/jmasm/1430453460
Srivastava, A. K., & Shalabh. (2001). Effect of measurement errors on the regression method of estimation in survey sampling. Journal of Statistical Research, 35(2), 35–44.
Sud, C., & Srivastava, S. K. (2000). Estimation of population mean in repeat surveys in the presence of measurement errors. Journal of the Indian Society of Agricultural Statistics, 53(2), 125–133.
Triveni, G. R. V., Danish, F., & Alrasheedi, M. (2025b). Application of Log-Type estimators for address-ing Non-Response in survey sampling using real datasets. Mathematics, 13(7), 1089. https://doi.org/10.3390/math13071089
Ünal, C., & Kadilar, C. (2019). Improved family of estimators using exponential function for the population mean in the presence of non-response. Communication in Statistics- Theory and Methods, 50(1), 237–248. https://doi.org/10.1080/03610926.2019.1634818
Zahid, E., & Shabbir, J. (2019). Estimation of finite population means a sensitive variable using dual auxiliary information in the presence of measurement errors. PLOS ONE, 14(2), e0212111. https://doi.org/10.1371/journal.pone.0212111
Zahid, E., Shabbir, J., Gupta, S., Onyango, R., & Saeed, S. (2022). A generalized class of estimators for sensitive variable in the presence of measurement error and non-response. PLoS ONE, 17(1), e0261561. https://doi.org/10.1371/journal.pone.0261561
Downloads
Published
Issue
Section
License
Copyright (c) 2025 SCOPUA Journal of Applied Statistical Research

This work is licensed under a Creative Commons Attribution 4.0 International License.























