Estimation of treatment effects in two sample problems under general biased sampling data

Fangfang Bai and Ruiyu Yang

Communications in Statistics - Theory and Methods, 2024, vol. 53, issue 22, 7829-7841

Abstract: General biased data frequently arises in various observational studies, either naturally or by design. The data is not representative of the target population, highlighting the importance of developing methods that address general biased data. This article primarily focuses on the estimation of treatment effects with general biased data. By employing the inverse probability weighting technique, a unified semiparametric estimating equation is constructed to derive an unbiased estimator. The large sample properties of the resulting estimator are established under some mild regularity conditions. Simulation studies and applications to the Oscar data and the heart transplant survival data are presented.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2023.2273208 (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:53:y:2024:i:22:p:7829-7841

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

DOI: 10.1080/03610926.2023.2273208

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 ().