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Invited commentary: G-Computation-lost in translation?

(2011) AMERICAN JOURNAL OF EPIDEMIOLOGY. 173(7). p.739-742
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Abstract
In this issue of the Journal, Snowden et al. (Am J Epidemiol. 2011;173(7):731-738) give a didactic explanation of G-computation as an approach for estimating the causal effect of a point exposure. The authors of the present commentary reinforce the idea that their use of G-computation is equivalent to a particular form of model-based standardization, whereby reference is made to the observed study population, a technique that epidemiologists have been applying for several decades. They comment on the use of standardized versus conditional effect measures and on the relative predominance of the inverse probability-of-treatment weighting approach as opposed to G-computation. They further propose a compromise approach, doubly robust standardization, that combines the benefits of both of these causal inference techniques and is not more difficult to implement.
Keywords
CAUSAL INFERENCE, MARGINAL STRUCTURAL MODELS, MORTALITY, DISEASE, air pollution, asthma, regression analysis, simulation

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Citation

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

Chicago
Vansteelandt, Stijn, and Niels Keiding. 2011. “Invited Commentary: G-Computation-lost in Translation?” American Journal of Epidemiology.
APA
Vansteelandt, S., & Keiding, N. (2011). Invited commentary: G-Computation-lost in translation? AMERICAN JOURNAL OF EPIDEMIOLOGY.
Vancouver
1.
Vansteelandt S, Keiding N. Invited commentary: G-Computation-lost in translation? AMERICAN JOURNAL OF EPIDEMIOLOGY. 2011. p. 739–42.
MLA
Vansteelandt, Stijn, and Niels Keiding. “Invited Commentary: G-Computation-lost in Translation?” AMERICAN JOURNAL OF EPIDEMIOLOGY 2011 : 739–742. Print.
@misc{1234526,
  abstract     = {In this issue of the Journal, Snowden et al. (Am J Epidemiol. 2011;173(7):731-738) give a didactic explanation of G-computation as an approach for estimating the causal effect of a point exposure. The authors of the present commentary reinforce the idea that their use of G-computation is equivalent to a particular form of model-based standardization, whereby reference is made to the observed study population, a technique that epidemiologists have been applying for several decades. They comment on the use of standardized versus conditional effect measures and on the relative predominance of the inverse probability-of-treatment weighting approach as opposed to G-computation. They further propose a compromise approach, doubly robust standardization, that combines the benefits of both of these causal inference techniques and is not more difficult to implement.},
  author       = {Vansteelandt, Stijn and Keiding, Niels},
  issn         = {0002-9262},
  keyword      = {CAUSAL INFERENCE,MARGINAL STRUCTURAL MODELS,MORTALITY,DISEASE,air pollution,asthma,regression analysis,simulation},
  language     = {eng},
  number       = {7},
  pages        = {739--742},
  series       = {AMERICAN JOURNAL OF EPIDEMIOLOGY},
  title        = {Invited commentary: G-Computation-lost in translation?},
  url          = {http://dx.doi.org/10.1093/aje/kwq474},
  volume       = {173},
  year         = {2011},
}

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