Invited commentary: G-Computation-Lost in Translation?

TY - JOUR

T1 - Invited commentary: G-Computation-Lost in Translation?

AU - Vansteelandt, Stijn

AU - Keiding, Niels

PY - 2011/4/1

Y1 - 2011/4/1

N2 - 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.

AB - 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.

U2 - 10.1093/aje/kwq474

DO - 10.1093/aje/kwq474

M3 - Comment/debate

SN - 0002-9262

VL - 173

SP - 739

EP - 742

JO - American Journal of Epidemiology

JF - American Journal of Epidemiology

IS - 7

ER -