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Jonathan M. Snowden, Sherri Rose, Kathleen M. Mortimer, Implementation of G-Computation on a Simulated Data Set: Demonstration of a Causal Inference Technique, American Journal of Epidemiology, Volume 173, Issue 7, 1 April 2011, Pages 731–738, https://doi.org/10.1093/aje/kwq472
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Abstract
The growing body of work in the epidemiology literature focused on G-computation includes theoretical explanations of the method but very few simulations or examples of application. The small number of G-computation analyses in the epidemiology literature relative to other causal inference approaches may be partially due to a lack of didactic explanations of the method targeted toward an epidemiology audience. The authors provide a step-by-step demonstration of G-computation that is intended to familiarize the reader with this procedure. The authors simulate a data set and then demonstrate both G-computation and traditional regression to draw connections and illustrate contrasts between their implementation and interpretation relative to the truth of the simulation protocol. A marginal structural model is used for effect estimation in the G-computation example. The authors conclude by answering a series of questions to emphasize the key characteristics of causal inference techniques and the G-computation procedure in particular.
