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Stijn Vansteelandt, Niels Keiding, Invited Commentary: G-Computation–Lost in Translation?, American Journal of Epidemiology, Volume 173, Issue 7, 1 April 2011, Pages 739–742, https://doi.org/10.1093/aje/kwq474
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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.
