- Tytuł:
- Missing data estimation based on the chaining technique in survey sampling
- Autorzy:
-
Singh Thakur, Narendra
Shukla, Diwakar - Powiązania:
- https://bibliotekanauki.pl/articles/2156986.pdf
- Data publikacji:
- 2022-12-15
- Wydawca:
- Główny Urząd Statystyczny
- Tematy:
-
estimation
missing data
chaining
imputation
bias
mean squared error (MSE)
factor type (F-T)
chain type estimator
double sampling - Opis:
- 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.
- Źródło:
-
Statistics in Transition new series; 2022, 23, 4; 91-111
1234-7655 - Pojawia się w:
- Statistics in Transition new series
- Dostawca treści:
- Biblioteka Nauki