Some improved and alternative imputation methods for finite population mean in presence of missing information
Garib Nath Singh,
Awadhesh K. Pandey and
Anup Kumar Sharma
Communications in Statistics - Theory and Methods, 2021, vol. 50, issue 19, 4401-4427
Abstract:
The crux of this study is to propose some modified and improved compromised imputation methods and their corresponding point estimators to estimate the population mean using information on an auxiliary variable in case of missing data problem under simple random sampling without replacement scheme. The properties of the suggested estimation procedures have been examined. Monte Carlo simulation study has been performed in order to show that the proposed class of estimators give better results in comparison to some of the existing estimators. Suitable recommendations are made to the survey practitioners.
Date: 2021
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2020.1713375 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:50:y:2021:i:19:p:4401-4427
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20
DOI: 10.1080/03610926.2020.1713375
Access Statistics for this article
Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe
More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().