Published

2023-01-01

Imputation of Missing Data Through Product Type Exponential Methods in Sampling Theory

Imputación de datos faltantes a través de métodos exponenciales de tipo de producto en la teoría del muestreo

DOI:

https://doi.org/10.15446/rce.v46n1.102308

Keywords:

Auxiliary variable, Product type estimator, Imputation (en)
Variable auxiliar, Estimador de tipo de producto, Imputación (es)

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Authors

  • Shakti Prasad National Institute of Technology, Arunachal Prades
  • Vinay Kumar Yadav National Institute of Technology, Arunachal Pradesh

 Some efficient product type exponential imputation methods are proposed in this article to tackle the problem of incomplete values in sampling theory. To investigate the effectiveness of proposed exponential methods, the behaviours of the considered estimators are compared in two scenarios: with and without nonresponse. The simulation studies show that the proposed resultant estimators outperform other existing estimators in this literature.

En este artículo se proponen algunos métodos eficientes de imputación exponencial de tipo de producto para abordar el problema de los valores incompletos en la teoría del muestreo. Para investigar la efectividad de los métodos exponenciales propuestos, se comparan los comportamientos de los estimadores considerados en dos escenarios: con y sin falta de respuesta. Los estudios de simulación muestran que los estimadores resultantes propuestos superan a otros estimadores existentes en esta literatura.

References

Ahmed, M., Al-Titi, O., Al-Rawi, Z. & Abu-Dayyeh, W. (2006), 'Estimation of a population mean using different imputation methods', Statistics in Transition 7(6), 1247-1264.

Diana, G. & Francesco Perri, P. (2010), 'Improved estimators of the population mean for missing data', Communications in Statistics-Theory and Methods 39(18), 3245-3251. DOI: https://doi.org/10.1080/03610920903009400

Gira, A. A. (2015), 'Estimation of population mean with a new imputation methods', Applied Mathematical Sciences 9(34), 1663-1672. DOI: https://doi.org/10.12988/ams.2015.5293

Heitjan, D. F. & Basu, S. (1996), 'Distinguishing missing at random and missing completely at random', The American Statistician 50(3), 207-213. DOI: https://doi.org/10.1080/00031305.1996.10474381

Hyunshik Lee, E. R. & Särndal, C. E. (1994), 'Experiments with variance estimation from survey data with imputed values', Journal of oficial Statistics 10(3), 231-243.

Kadilar, C. & Cingi, H. (2008), 'Estimators for the population mean in the case of missing data', Communications in Statistics-Theory and Methods 37(14), 2226-2236. DOI: https://doi.org/10.1080/03610920701855020

Lee, H., Rancourt, E. & Sarndal, C. (1995), 'Variance estimation in the presence of imputed data for the generalized estimation system', American Statistical Association (Social Survey Research Methods Section) pp. 384-389.

Pandey, B. & Dubey, V. (1988), 'Modified product estimator using coefficient of variation of auxiliary variate', Assam Statistical Rev 2(2), 64-66.

Prasad, S. (2017), 'Ratio exponential type estimators with imputation for missing data in sample surveys', Model Assisted Statistics and Applications 12(2), 95-106. DOI: https://doi.org/10.3233/MAS-170386

Prasad, S. (2018a), 'Product exponential method of imputation in sample surveys', Statistics in Transition. New Series 19(1), 159-166. DOI: https://doi.org/10.21307/stattrans-2018-010

Prasad, S. (2018b), 'A study on new methods of ratio exponential type imputation in sample surveys', Hacettepe Journal of Mathematics and Statistics 47(5), 1281-1301.

Prasad, S. (2019), 'Exponential method of imputation for non-response in sample surveys', Pakistan Journal of Statistics 35(2), 97-107.

Prasad, S. (2021), 'Some compromised exponential ratio type imputation methods in simple random sampling', Proceedings of the National Academy of Sciences, India Section A: Physical Sciences 91(2), 337-349. DOI: https://doi.org/10.1007/s40010-020-00719-4

Sande, I. G. (1979), 'A personal view of hot-deck imputation procedures', Survey Methodology 5(2), 238-258.

Singh, G., Maurya, S., Khetan, M. & Kadilar, C. (2016), 'Some imputation methods for missing data in sample surveys', Hacettepe Journal of Mathematics and Statistics 45(6), 1865-1880.

Singh, G., Priyanka, K., Kim, J.-M. & Singh, S. (2010), 'Estimation of population mean using imputation techniques in sample surveys', Journal of the Korean Statistical Society 39(1), 67-74. DOI: https://doi.org/10.1016/j.jkss.2009.04.002

Singh, R. & Mangat, N. S. (2013), Elements of survey sampling, Vol. 15, Springer Science & Business Media.

Singh, S. (2003), Advanced Sampling Theory With Applications: How Michael Selected Amy, Vol. 2, Springer Science & Business Media. DOI: https://doi.org/10.1007/978-94-007-0789-4

Singh, S. (2009), 'A new method of imputation in survey sampling', Statistics 43(5), 499-511. DOI: https://doi.org/10.1080/02331880802605114

Singh, S. & Deo, B. (2003), 'Imputation by power transformation', Statistical Papers 44(4), 555-579. DOI: https://doi.org/10.1007/BF02926010

Singh, S. & Horn, S. (2000), 'Compromised imputation in survey sampling', Metrika 51(3), 267-276. DOI: https://doi.org/10.1007/s001840000054

Team, R. C. et al. (2021), 'R: A language and environment for statistical computing'. http://www. R-project. org/

Toutenburg, H., Srivastava, V. et al. (2008), 'Amputation versus imputation of missing values through ratio method in sample surveys', Statistical Papers 49(2), 237-247. DOI: https://doi.org/10.1007/s00362-006-0009-4

How to Cite

APA

Prasad, S. and Yadav, V. K. (2023). Imputation of Missing Data Through Product Type Exponential Methods in Sampling Theory. Revista Colombiana de Estadística, 46(1), 111–127. https://doi.org/10.15446/rce.v46n1.102308

ACM

[1]
Prasad, S. and Yadav, V.K. 2023. Imputation of Missing Data Through Product Type Exponential Methods in Sampling Theory. Revista Colombiana de Estadística. 46, 1 (Jan. 2023), 111–127. DOI:https://doi.org/10.15446/rce.v46n1.102308.

ACS

(1)
Prasad, S.; Yadav, V. K. Imputation of Missing Data Through Product Type Exponential Methods in Sampling Theory. Rev. colomb. estad. 2023, 46, 111-127.

ABNT

PRASAD, S.; YADAV, V. K. Imputation of Missing Data Through Product Type Exponential Methods in Sampling Theory. Revista Colombiana de Estadística, [S. l.], v. 46, n. 1, p. 111–127, 2023. DOI: 10.15446/rce.v46n1.102308. Disponível em: https://revistas.unal.edu.co/index.php/estad/article/view/102308. Acesso em: 31 may. 2024.

Chicago

Prasad, Shakti, and Vinay Kumar Yadav. 2023. “Imputation of Missing Data Through Product Type Exponential Methods in Sampling Theory”. Revista Colombiana De Estadística 46 (1):111-27. https://doi.org/10.15446/rce.v46n1.102308.

Harvard

Prasad, S. and Yadav, V. K. (2023) “Imputation of Missing Data Through Product Type Exponential Methods in Sampling Theory”, Revista Colombiana de Estadística, 46(1), pp. 111–127. doi: 10.15446/rce.v46n1.102308.

IEEE

[1]
S. Prasad and V. K. Yadav, “Imputation of Missing Data Through Product Type Exponential Methods in Sampling Theory”, Rev. colomb. estad., vol. 46, no. 1, pp. 111–127, Jan. 2023.

MLA

Prasad, S., and V. K. Yadav. “Imputation of Missing Data Through Product Type Exponential Methods in Sampling Theory”. Revista Colombiana de Estadística, vol. 46, no. 1, Jan. 2023, pp. 111-27, doi:10.15446/rce.v46n1.102308.

Turabian

Prasad, Shakti, and Vinay Kumar Yadav. “Imputation of Missing Data Through Product Type Exponential Methods in Sampling Theory”. Revista Colombiana de Estadística 46, no. 1 (January 18, 2023): 111–127. Accessed May 31, 2024. https://revistas.unal.edu.co/index.php/estad/article/view/102308.

Vancouver

1.
Prasad S, Yadav VK. Imputation of Missing Data Through Product Type Exponential Methods in Sampling Theory. Rev. colomb. estad. [Internet]. 2023 Jan. 18 [cited 2024 May 31];46(1):111-27. Available from: https://revistas.unal.edu.co/index.php/estad/article/view/102308

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CrossRef Cited-by

CrossRef citations6

1. Vinay Kumar Yadav, Shakti Prasad. (2024). Generalized class of factor type exponential imputation techniques for population mean using simulation approach. Journal of Statistical Computation and Simulation, , p.1. https://doi.org/10.1080/00949655.2024.2310699.

2. Shashi Bhushan, Anoop Kumar, Rohini Pokhrel, M. E. Bakr, Getachew Tekle Mekiso. (2024). Design based synthetic imputation methods for domain mean. Scientific Reports, 14(1) https://doi.org/10.1038/s41598-024-53909-0.

3. Vinay Kumar Yadav, Shakti Prasad. (2024). Neutrosophic Estimators for Estimating the Population Mean in Survey Sampling. Measurement: Interdisciplinary Research and Perspectives, , p.1. https://doi.org/10.1080/15366367.2023.2267835.

4. Vinay Kumar Yadav, Shakti Prasad. (2023). A simulation based optimization of factor-type exponential estimators in sample surveys with coefficients of variation and kurtosis. Franklin Open, 5, p.100050. https://doi.org/10.1016/j.fraope.2023.100050.

5. Shashi Bhushan, Anoop Kumar. (2024). Ranked set sampling imputation methods in presence of correlated measurement errors. Communications in Statistics - Theory and Methods, , p.1. https://doi.org/10.1080/03610926.2024.2352031.

6. Shashi Bhushan, Anoop Kumar, Rohini Pokhrel. (2024). Synthetic imputation methods for domain mean under simple random sampling. Franklin Open, 7, p.100101. https://doi.org/10.1016/j.fraope.2024.100101.

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