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Doubly robust estimation of attributable fractions in survival analysis

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Abstract
The attributable fraction is a commonly used measure that quantifies the public health impact of an exposure on an outcome. It was originally defined for binary outcomes, but an extension has recently been proposed for right-censored survival time outcomes; the so-called attributable fraction function. A maximum likelihood estimator of the attributable fraction function has been developed, which requires a model for the outcome. In this paper, we derive a doubly robust estimator of the attributable fraction function. This estimator requires one model for the outcome, and one joint model for the exposure and censoring. The estimator is consistent if either model is correct, not necessarily both.
Keywords
Attributable fraction, causal inference, cohort studies, Cox proportional hazards model, doubly robust estimation, CAUSAL INFERENCE, AUTISM, EVENT

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

Chicago
Sjolander, Arvid, and Stijn Vansteelandt. 2017. “Doubly Robust Estimation of Attributable Fractions in Survival Analysis.” Statistical Methods in Medical Research 26 (2): 948–969.
APA
Sjolander, Arvid, & Vansteelandt, S. (2017). Doubly robust estimation of attributable fractions in survival analysis. STATISTICAL METHODS IN MEDICAL RESEARCH, 26(2), 948–969.
Vancouver
1.
Sjolander A, Vansteelandt S. Doubly robust estimation of attributable fractions in survival analysis. STATISTICAL METHODS IN MEDICAL RESEARCH. 2017;26(2):948–69.
MLA
Sjolander, Arvid, and Stijn Vansteelandt. “Doubly Robust Estimation of Attributable Fractions in Survival Analysis.” STATISTICAL METHODS IN MEDICAL RESEARCH 26.2 (2017): 948–969. Print.
@article{8545454,
  abstract     = {The attributable fraction is a commonly used measure that quantifies the public health impact of an exposure on an outcome. It was originally defined for binary outcomes, but an extension has recently been proposed for right-censored survival time outcomes; the so-called attributable fraction function. A maximum likelihood estimator of the attributable fraction function has been developed, which requires a model for the outcome. In this paper, we derive a doubly robust estimator of the attributable fraction function. This estimator requires one model for the outcome, and one joint model for the exposure and censoring. The estimator is consistent if either model is correct, not necessarily both.},
  author       = {Sjolander, Arvid and Vansteelandt, Stijn},
  issn         = {0962-2802},
  journal      = {STATISTICAL METHODS IN MEDICAL RESEARCH},
  keyword      = {Attributable fraction,causal inference,cohort studies,Cox proportional hazards model,doubly robust estimation,CAUSAL INFERENCE,AUTISM,EVENT},
  language     = {eng},
  number       = {2},
  pages        = {948--969},
  title        = {Doubly robust estimation of attributable fractions in survival analysis},
  url          = {http://dx.doi.org/10.1177/0962280214564003},
  volume       = {26},
  year         = {2017},
}

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