A note on the properties of estimators in missing data analysis

Tadayoshi Fushiki

Communications in Statistics - Theory and Methods, 2022, vol. 51, issue 17, 6144-6149

Abstract: In the missing mechanism, missing at random (MAR) is sometimes assumed when data has missing values. When MAR holds and the true distribution belongs to the assumed statistical model, the maximum likelihood estimator based on the observed data has consistency. Based on a weaker condition than MAR, this study investigates the properties of the estimators obtained by applying the maximum likelihood method and the Bayesian method when the true distribution does not belong to the statistical model.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2020.1854305 (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:51:y:2022:i:17:p:6144-6149

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2020.1854305

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 ().