Correo Electrónico
DNINFOA - SIA
Bibliotecas
Convocatorias
Identidad U.N.
Published
Determination of the Effect of Measurement Error using Factor Type Estimator in Two Phase Sampling
Determinación del efecto del error de medición utilizando un estimador de tipo factor en muestreo bifásico
DOI:
https://doi.org/10.15446/rce.v49n1.119457Keywords:
Bias, Estimation, Factor-type estimator, Measurement error, MSE, Two-phase sampling (en)Error de medición, Estimación, Estimador tipo factorial, MSE, Muestreo bifásico, Sesgo (es)
Downloads
In this study, factor-type estimator is used for estimating the finite population mean under two-phase sampling scheme in the presence of measurement error. The Bias and Mean Squared Error (MSE) of factor-type estimator are derived in this paper and compared with the existing estimators in literature. Then, the conditions under which the suggested estimator is better than the existing estimators in terms of efficiency are provided here. Theoretical as well as real data comparison of factor-type estimator are done to get precious result.
En este estudio, se utiliza un estimador factorial para estimar la media de una población finita bajo un esquema de muestreo bifásico en presencia de error de medición. El sesgo y el error cuadrático medio (EMM) del estimador factorial se derivan en este trabajo y se comparan con los estimadores existentes en la literatura. Posteriormente, se presentan las condiciones bajo las cuales el estimador sugerido es superior a los estimadores existentes en términos de eficiencia. Se realizan comparaciones teóricas y reales del estimador factorial para obtener resultados valiosos.
References
Buonaccorsi, J. P. (2010). Measurement error: Models, methods and applications. Chapman and Hall/CRC, New York.
Hansen, M. H., & Hurwitz, W. N. (1946). The problem of nonresponse in sample surveys. Journal of the American Statistical Association, 41, 517–529.
Kadilar, C., & Cingi, H. (2006). Ratio estimators for the population variance in simple and stratified random sampling. Applied Mathematics and Computation, 173, 1047–1059.
Khare, B. B., & Sinha, R. R. (2009). On class of estimators for population mean using multi-auxiliary characters in the presence of non-response. Statistics in Transition: New Series, 10, 3–14.
Manisha, & Singh, R. K. (2001). An estimation of population mean in the presence of measurement errors. Journal of the Indian Society of Agricultural Statistics, 54, 13–18.
Manisha, & Singh, R. K. (2002). Role of regression estimator involving measurement errors. Brazilian Journal of Probability and Statistics, 16, 39–46.
Muhammad, I., Zakari, Y., & Audu, A. (2021). An alternative class of ratio-regression-type estimator under two-phase sampling scheme. CBN Journal of Applied Statistics, 12, 1–26.
Ozgul, N., & Cingi, H. (2014). A new class of exponential regression cum ratio estimator in two-phase sampling. Hacettepe Journal of Mathematics and Statistics, 43, 131–140.
Sabir, S., Sanaullah, A., & Gupta, S. (2022). Estimation of mean considering the joint influence of measurement errors and non-response in two-phase sampling designs. Journal of the National Science Foundation of Sri Lanka, 50, 13.
Shukla, D., Pathak, S., & Thakur, N. S. (2012a). Classes of factor-type estimator in presence of measurement error. Journal of Modern Applied Statistical Methods, 11, 336–347.
Shukla, D., Pathak, S., & Thakur, N. S. (2012b). An estimator for mean estimation in presence of measurement error. Research and Reviews: A Journal of Statistics, 2, 1–8.
Singh, H. P., & Karpe, N. (2009). On the estimation of ratio and product of two population means using supplementary information in presence of measurement errors. Statistica, 69, 27–47.
Singh, H. P., & Karpe, N. (2010). Effect of measurement errors on the separate and combined ratio and product estimators in stratified random sampling. Journal of Modern Applied Statistical Methods, 9.
Singh, H. P., & Vishwakarma, G. K. (2007). Modified exponential ratio and product estimators for finite population mean in two-phase sampling. Austrian Journal of Statistics, 36, 217–225.
Singh, N., & Vishwakarma, G. K. (2019). A generalized class of estimator of population mean with the combined effect of measurement errors and non-response in sample survey. Revista Investigación Operacional, 40, 275–285.
Singh, R., Mishra, M., & Mishra, M. (2020). Estimation in stratified random sampling in the presence of errors. Revista Investigación Operacional, 41, 125–137.
Singh, V. K., & Shukla, D. (1987). One-parameter family of factor-type ratio estimator. Metron, 45(1–2), 273–283.
Sinha, R. R., & Khare, B. B. (2011). Estimation of population mean using multi-auxiliary characters with subsampling the non-respondents. Statistics in Transition: New Series, 12, 45–56.
Wu, C., & Luan, Y. (2003). Optimal calibration estimators under two-phase sampling. Journal of Official Statistics, 19, 119–131.
Yadav, A., Thakur, N. S., & Pareek, S. (2024). Determining the effect of measurement errors and estimation of mean by factor-type estimator in simple random sampling. Journal of Modern Applied Statistical Methods, 23, 6.
Yadav, A., Thakur, N. S., & Pareek, S. (2025). Ratio and product type estimators in post-stratified sampling with measurement errors. Model Assisted Statistics and Applications.
How to Cite
APA
ACM
ACS
ABNT
Chicago
Harvard
IEEE
MLA
Turabian
Vancouver
Download Citation
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
