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Doubly robust estimation of attributable fractions

(2011) BIOSTATISTICS. 12(1). p.112-121
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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.
Keywords
MODELS, DISEASE, RISK, Attributable fraction, attributable risk, doubly robust estimation, excess fraction, inverse probability weighting, maximum likelihood

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Citation

Please use this url to cite or link to this publication:

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.
@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},
}

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