Estimation of Population Mean Using Some Improved Imputation Methods for Missing Data in Sample Surveys
Özet
Abstract.: In this research article, we present novel imputation methods designed to address missing data challenges in sample surveys. We then introduce innovative estimation procedures for calculating population means based on these methods. Our study thoroughly examines the properties of these new estimation procedures, assessing their biases and mean square errors. Through the use of both real and simulated data sets, we demonstrate the superior performance of our proposed estimators compared to existing methods in similar scenarios. In conclusion, we offer practical recommendations for survey practitioners.
Anahtar Kelimeler
RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/gumushane/12433Resmi atıflarda kullanılan kalıcı adresAtıflar
- Scopus
- 8
- WoS
- 9
- OpenAlex
- 11
Tam Kayıt
| Alan | Değer | Dil |
|---|---|---|
| dc.contributor.author | Pandey, M.K. | |
| dc.contributor.author | Singh, G.N. | |
| dc.contributor.author | Zaman, Togla | |
| dc.date.accessioned | 2026-10-22T10:20:06.694076616Z | |
| dc.date.available | 2026-10-22T10:20:06.694076616Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | Abstract.: In this research article, we present novel imputation methods designed to address missing data challenges in sample surveys. We then introduce innovative estimation procedures for calculating population means based on these methods. Our study thoroughly examines the properties of these new estimation procedures, assessing their biases and mean square errors. Through the use of both real and simulated data sets, we demonstrate the superior performance of our proposed estimators compared to existing methods in similar scenarios. In conclusion, we offer practical recommendations for survey practitioners. | |
| dc.description.sponsorship | IIlinois State Museum, ISM | |
| dc.identifier.doi | 10.1080/03610926.2024.2369314 | |
| dc.identifier.eissn | 1532-415X | |
| dc.identifier.endpage | 2392 | |
| dc.identifier.issn | 0361-0926 | |
| dc.identifier.issue | 8 | |
| dc.identifier.scopus | 2-s2.0-86000382742 | |
| dc.identifier.startpage | 2378 | |
| dc.identifier.uri | https://rdlopen.rawdatalibrary.net/r/gumushane/12433 | |
| dc.identifier.volume | 54 | |
| dc.identifier.wos | WOS:001276050200001 | |
| dc.language.iso | en | |
| dc.publisher | Taylor and Francis Ltd. | |
| dc.relation.ispartof | Communications in Statistics - Theory and Methods | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | bias | |
| dc.subject | Imputation | |
| dc.subject | mean squared error (MSE) | |
| dc.subject | percent relative efficiency (PRE) | |
| dc.subject.classification | Statistics & Probability | |
| dc.subject.classification | Mathematics | |
| dc.subject.other | Abstracting | |
| dc.subject.other | Population statistics | |
| dc.subject.other | Bias | |
| dc.subject.other | Data challenges | |
| dc.subject.other | Estimation procedures | |
| dc.subject.other | Imputation | |
| dc.subject.other | Imputation methods | |
| dc.subject.other | Mean squared error | |
| dc.subject.other | Missing data | |
| dc.subject.other | Percent relative efficiencies | |
| dc.subject.other | Percent relative efficiency | |
| dc.subject.other | Mean square error | |
| dc.title | Estimation of Population Mean Using Some Improved Imputation Methods for Missing Data in Sample Surveys | |
| dc.type | Article | |
| dspace.entity.type | Publication | |
| rdl.citation.openalex | 11 | |
| rdl.citation.scopus | 8 | |
| rdl.citation.wos | 9 | |
| rdl.oa.status | closed | |
| rdl.scopus.quartile | Q3 | |
| rdl.source.index | SCOPUS | |
| rdl.source.index | WOS | |
| rdl.wos.index | Science Citation Index Expanded (SCI-EXPANDED) |
