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Author
Thakur Narendra Singh (Govt. Adarsh Girls College, Sheopur (M.P.), India), Shukla Diwakar (Dr. Harisingh Gour Central University)
Title
Missing Data Estimation Based on the Chaining Technique in Survey Sampling
Source
Statistics in Transition, 2022, vol. 23, nr 4, s. 91-111, aneks, tab., bibliogr. 41 poz.
Keyword
Estymacja, Estymatory, Badania statystyczne
Estimation, Estimators, Statistical surveys
Note
summ.
Mathematical Subject Code: 62D05
Abstract
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)
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The Library of Warsaw School of Economics
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Bibliography
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ISSN
1234-7655
Language
eng
URI / DOI
http://dx.doi.org/10.2478/stattrans-2022-0044
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