Estimation of a Generalized Treatment Effect in a Control Group Versus Treatment Group Design
Daniel R. Jeske
The American Statistician, 2025, vol. 79, issue 2, 167-172
Abstract:
A control group versus treatment group design is considered where the responses in the treatment group are modeled as a two-component mixture model that accounts for the possibility that only a fraction of the patients in the treated group will respond to the treatment. In this setting, the treatment effect is generalized to include both the fraction of treated patients that respond to the treatment and the magnitude of the response. Two alternative correlated and biased estimators are combined to yield an estimator that is preferable to either one of the estimators individually. The combined estimator is demonstrated on an illustrative blood pressure dataset.
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00031305.2024.2422933 (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:amstat:v:79:y:2025:i:2:p:167-172
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UTAS20
DOI: 10.1080/00031305.2024.2422933
Access Statistics for this article
The American Statistician is currently edited by Eric Sampson
More articles in The American Statistician from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().