Interval estimation for treatment effects using propensity score matching.
Publication
, Journal Article
Hill, J; Reiter, JP
Published in: Statistics in medicine
July 2006
In causal studies without random assignment of treatment, causal effects can be estimated using matched treated and control samples, where matches are obtained using estimated propensity scores. Propensity score matching can reduce bias in treatment effect estimators in cases where the matched samples have overlapping covariate distributions. Despite its application in many applied problems, there is no universally employed approach to interval estimation when using propensity score matching. In this article, we present and evaluate approaches to interval estimation when using propensity score matching.
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Published In
Statistics in medicine
DOI
EISSN
1097-0258
ISSN
0277-6715
Publication Date
July 2006
Volume
25
Issue
13
Start / End Page
2230 / 2256
Related Subject Headings
- Treatment Outcome
- Statistics & Probability
- Socioeconomic Factors
- Male
- Infant, Premature
- Infant, Newborn
- Infant, Low Birth Weight
- Infant
- Humans
- Female
Citation
APA
Chicago
ICMJE
MLA
NLM
Hill, J., & Reiter, J. P. (2006). Interval estimation for treatment effects using propensity score matching. Statistics in Medicine, 25(13), 2230–2256. https://doi.org/10.1002/sim.2277
Hill, Jennifer, and Jerome P. Reiter. “Interval estimation for treatment effects using propensity score matching.” Statistics in Medicine 25, no. 13 (July 2006): 2230–56. https://doi.org/10.1002/sim.2277.
Hill J, Reiter JP. Interval estimation for treatment effects using propensity score matching. Statistics in medicine. 2006 Jul;25(13):2230–56.
Hill, Jennifer, and Jerome P. Reiter. “Interval estimation for treatment effects using propensity score matching.” Statistics in Medicine, vol. 25, no. 13, July 2006, pp. 2230–56. Epmc, doi:10.1002/sim.2277.
Hill J, Reiter JP. Interval estimation for treatment effects using propensity score matching. Statistics in medicine. 2006 Jul;25(13):2230–2256.
Published In
Statistics in medicine
DOI
EISSN
1097-0258
ISSN
0277-6715
Publication Date
July 2006
Volume
25
Issue
13
Start / End Page
2230 / 2256
Related Subject Headings
- Treatment Outcome
- Statistics & Probability
- Socioeconomic Factors
- Male
- Infant, Premature
- Infant, Newborn
- Infant, Low Birth Weight
- Infant
- Humans
- Female