Missing Data Estimation Based on the Chaining Technique in Survey Sampling

• Autorzy: Narendra Singh Thakur , Diwakar Shukla
• Języki publikacji: EN

Abstrakty

EN

Sample surveys are often affected by missing observations and non-response caused by the respondents' refusal or unwillingness to provide the requested information or due to their memory failure. In order to substitute the missing data, a procedure called imputation is applied, which uses the available data as a tool for the replacement of the missing values. Two auxiliary variables create a chain which is used to substitute the missing part of the sample. The aim of the paper is to present the application of the Chain-type factor estimator as a means of source imputation for the non-response units in an incomplete sample. The proposed strategies were found to be more efficient and bias-controllable than similar estimation procedures described in the relevant literature. These techniques could also be made nearly unbiased in relation to other selected parametric values. The findings are supported by a numerical study involving the use of a dataset, proving that the proposed techniques outperform other similar ones. (original abstract)

Słowa kluczowe

EN

Estimation; Estimators; Statistical surveys

PL

Estymacja; Estymatory; Badania statystyczne

• Czasopismo: Statistics in Transition
• Rocznik: 2022
• Tom: 23
• Numer: nr 4
• Strony: 91--111

Twórcy

autor

Narendra Singh Thakur

• Govt. Adarsh Girls College, Sheopur (M.P.), India

autor

Diwakar Shukla

• Dr. Harisingh Gour Central University

Bibliografia

• Ahmed, M. S., Al-Titi, O., Al-Rawi, Z. and Abu-Dayyeh, W., (2006). Estimation of a population mean using different imputation methods. Statistics in Transition, 7, 6, pp. 1247-1264.
• Al-Jararha, J., Ahmed, M. S., (2002). The class of chain estimators for a finite population variance using double sampling. Information and Management Sciences, 13(2), pp. 13-18.
• Bhaskaran, K., Smeeth, L., (2014). What is the difference between missing completely at random and missing at random? International Journal of Epidemiology, 43(4), pp. 1336-1339.
• Bose, C., (1943). Note on the sampling error in the method of double sampling. Sankhya, 6, 330.
• Chand, L., (1975). Some ratio-type estimators based on two or more auxiliary variables unpublished Ph.D. Thesis, IOWA State University, Ames, Iowa, U.S.A.
• Choudhury, S., Singh, B. K., (2012). A class of chain ratio-cum-dual to ratio type estimator with two auxiliary characters under double sampling in sample surveys. Statistics in Transition-new series, 13(3), pp. 519-536.
• Cochran, W. G., (2005). Sampling Techniques. John Wiley and Sons, New York.
• Doretti, M., Geneletti, S. and Stanghellini, E., (2018). Missing data: A unified taxonomy guided by conditional independence. International Statistical Review, 86(2), pp. 189-204.
• Heitjan, D. F., Basu, S., (1996). Distinguishing 'missing at random' and 'missing completely at random'. The American Statistician, 50, pp. 207-213.
• Kadilar, C., Cingi, H., (2003). A study on the chain ratio-type estimator. Hacettepe Journal of Mathematics and Statistics, 32, pp. 105-108.
• Kiregyera, B., (1980). A chain ratio-type estimator in finite population double sampling using two auxiliary variables. Metrika, 27 (1), pp. 217-223.
• Kiregyera, B., (1984). Regression type estimators using two auxiliary variables and the model of double sampling from finite population. Metrika, 31, pp. 215-226.
• Kumar, M., Bahl, S., (2006). Class of dual to ratio estimators for double sampling. Statistical Papers, 47, pp. 319-326.
• Little, R. J. A., Rubin, D. B., (1987). Statistical analysis with missing data, New York: John Wiley & Sons, Inc.
• Pandey, R., Thakur, N. S. and Yadav, K., (2016). Adapted factor-type imputation strategies. Journal of Scientific Research, J. Sci. Res., 8(3), pp. 321-339.
• Pandey, R., Thakur, N. S. and Yadav, K., (2015). Estimation of population mean using exponential ratio type imputation method under survey non-response. Journal of the Indian Statistical Association, Vol.53 No. 1 & 2, pp. 89-107.
• Pradhan, B. K., (2005). A chain regression estimator in two phase sampling using multiauxiliary information. Bulletin of the Malaysian Mathematical Sciences Society (2), 28(1), pp. 81-86.
• Rao, J. N. K., Sitter, R. R., (1995). Variance estimation under two-phase sampling with application to imputation for missing data. Biometrika, 82, pp. 453-460.
• Reddy, V. N., (1978). A study on the use of prior knowledge on certain population parameters in estimation. Sankhya, C, 40, pp. 29-37.
• Rubin, D. B., (1976). Inference and missing data. Biometrika, 63, pp. 581-593.
• Seaman, S., Galati, J., Jackson, D. and Carlin, J., (2013). What is meant by "Missing at Random"? Statistical Science, 28(2), pp. 257-268.
• Sharma, B., Tailor, R., (2010). A new ratio-cum-dual to ratio estimator of finite population mean in simple random sampling. Global Journal of Science Frontier Research, 10(1), pp. 27-31.
• Shukla, D., (2002). F-T estimator under two-phase sampling. Metron, 59, 1-2, pp. 253- 263.
• Shukla, D., Thakur, N. S., Pathak, S. and Rajput, D. S., (2009). Estimation of mean under imputation of missing data using factor type estimator in two-phase sampling. Statistics in Transition, Vol. 10, No. 3, pp. 397-414.
• Shukla, D., Thakur, N. S., (2008). Estimation of mean with imputation of missing data Using Factor Type Estimator. Statistics in Transition, 9, 1, pp. 33-48
• Shukla, D., Singh, V. K. and Singh, G. N., (1991). On the use of transformation in factor type estimator. Metron, 49(1-4), pp. 359-361.
• Singh, H. P., Espejo, M. R., (2007). Double sampling ratio-product estimator of a finite population mean in sampling surveys. Journal of Applied Statistics, 34(1), pp. 71- 85.
• Singh, H. P., Mathur, N. and Chandra, P., (2009). A chain-type estimator for population variance using auxiliary variables in two-phase sampling. Statistics in Transitionnew series, 10(1), pp. 75-84.
• Singh, S., Horn, S., (2000). Compromised imputation in survey sampling. Metrika, 51, pp. 266-276.
• Singh, S., Singh, H. P. and Upadhyaya, L. N., (2006). Chain ratio and regression type estimators for median estimation in survey sampling. Statistical Papers, 48, pp. 23- 46.
• Singh, V. K., Shukla, D., (1987). One parameter family of factor-type ratio estimator. Metron, 45, 1-2, pp. 273-283.
• Singh, V. K., Shukla, D., (1993). An efficient one parameter family of factor - type estimator in sample survey. Metron, 51, 1-2, pp. 139-159.
• Singh, V. K., Singh, G. N., (1991). Chain type estimator with two auxiliary variables under double sampling scheme. Metron, 49, pp. 279-289.
• Singh, V. K., Singh, B. K. and Singh, G. N., (1993). An efficient class of dual to ratio estimators using two auxiliary characteristics. Journal of Scientific Research, 43, pp. 219-228.
• Singh, V. K., Singh, G. N. and Shukla, D., (1994). A class of chain ratio estimator with two auxiliary variables under double sampling scheme. Sankhya, Ser. B., 46, 2, pp. 209-221.
• Srivastava, S. K., Jhajj, H. S., (1980). A class of estimators using auxiliary information for estimating finite population variance. Sankhya, 42, pp. 87-96.
• Srivastava, S. R., Khare, B. B. and Srivastava, S. R., (1990). A generalized chain ratio estimator for mean of finite population. Journal of Indian Society of Agricultural Statistics, 42(I), pp. 108-117.
• Srivenkataramana, T., (1980). A dual to ratio estimator in sample surveys. Biometrika, 67(1), pp. 199-204.
• Sukhatme, B. V., Chand, L., (1977). Multivariate ratio-type estimators, Proceeding of American Statistical Association. Social Statistics Section, pp. 927-931.
• Sukhatme, P. V., Sukhatme, B. V., Sukhatme, S. and Ashok, C., (1984). Sampling Theory of Surveys with Applications. Iowa State University Press, I.S.A.S. Publication, New Delhi.
• Weeks, M., (1999). Methods of imputation for missing data (fifth draft), Faculty of Economics and Politics and Department of Applied Econometrics. University of Cambridge, Cambridge, UK.

Identyfikatory

DOI

10.2478/stattrans-2022-0044