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2022 | 23 | nr 4 | 91--111
Tytuł artykułu

Missing Data Estimation Based on the Chaining Technique in Survey Sampling

Warianty tytułu
Języki publikacji
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)
Opis fizyczny
  • Govt. Adarsh Girls College, Sheopur (M.P.), India
  • Dr. Harisingh Gour Central University
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