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Doubly robust estimation of attributable fractions

Arvid Sjolander and Stijn Vansteelandt UGent (2011) BIOSTATISTICS. 12(1). p.112-121
abstract
The attributable fraction (AF) is a widely used measure to assess the impact of an exposure on a disease. It is commonly estimated through maximum likelihood, which requires a regression model for the outcome. Recently, it was demonstrated that the AF can also be estimated through inverse probability weighting, which requires a model for the exposure. In this paper, we derive doubly robust estimators for the AF. These estimators require one model for the outcome and one model for the exposure and are consistent if either model is correct, not necessarily both. We consider both cohort/cross-sectional studies and case-control studies.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
MODELS, DISEASE, RISK, Attributable fraction, attributable risk, doubly robust estimation, excess fraction, inverse probability weighting, maximum likelihood
journal title
BIOSTATISTICS
Biostatistics
volume
12
issue
1
pages
112 - 121
Web of Science type
Article
Web of Science id
000285625800008
JCR category
STATISTICS & PROBABILITY
JCR impact factor
2.145 (2011)
JCR rank
8/116 (2011)
JCR quartile
1 (2011)
ISSN
1465-4644
DOI
10.1093/biostatistics/kxq049
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1234518
handle
http://hdl.handle.net/1854/LU-1234518
date created
2011-05-24 16:19:20
date last changed
2016-12-19 15:42:48
@article{1234518,
  abstract     = {The attributable fraction (AF) is a widely used measure to assess the impact of an exposure on a disease. It is commonly estimated through maximum likelihood, which requires a regression model for the outcome. Recently, it was demonstrated that the AF can also be estimated through inverse probability weighting, which requires a model for the exposure. In this paper, we derive doubly robust estimators for the AF. These estimators require one model for the outcome and one model for the exposure and are consistent if either model is correct, not necessarily both. We consider both cohort/cross-sectional studies and case-control studies.},
  author       = {Sjolander, Arvid and Vansteelandt, Stijn},
  issn         = {1465-4644},
  journal      = {BIOSTATISTICS},
  keyword      = {MODELS,DISEASE,RISK,Attributable fraction,attributable risk,doubly robust estimation,excess fraction,inverse probability weighting,maximum likelihood},
  language     = {eng},
  number       = {1},
  pages        = {112--121},
  title        = {Doubly robust estimation of attributable fractions},
  url          = {http://dx.doi.org/10.1093/biostatistics/kxq049},
  volume       = {12},
  year         = {2011},
}

Chicago
Sjolander, Arvid, and Stijn Vansteelandt. 2011. “Doubly Robust Estimation of Attributable Fractions.” Biostatistics 12 (1): 112–121.
APA
Sjolander, Arvid, & Vansteelandt, S. (2011). Doubly robust estimation of attributable fractions. BIOSTATISTICS, 12(1), 112–121.
Vancouver
1.
Sjolander A, Vansteelandt S. Doubly robust estimation of attributable fractions. BIOSTATISTICS. 2011;12(1):112–21.
MLA
Sjolander, Arvid, and Stijn Vansteelandt. “Doubly Robust Estimation of Attributable Fractions.” BIOSTATISTICS 12.1 (2011): 112–121. Print.