- 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)
- Accessibility
- The Main Library of the Cracow University of Economics
The Library of Warsaw School of Economics
The Library of University of Economics in Katowice - Full text
- Show
- Bibliography
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- Cited by
- ISSN
- 1234-7655
- Language
- eng
- URI / DOI
- http://dx.doi.org/10.2478/stattrans-2022-0044