Robins' generalized methods (g methods) provide consistent estimates of contrasts (e.g. differences, ratios) of potential outcomes under a less restrictive set of identification conditions than do standard regression methods (e.g. linear, logistic, Cox regression). Uptake of g methods by epidemiologists has been hampered by limitations in understanding both conceptual and technical details. We present a simple worked example that illustrates basic concepts, while minimizing technical complications.
Keywords: G Estimation; G Formula; G Methods; Inverse Probability Weighting; Marginal Structural Model; Monte Carlo Estimation; Structural Nested Model.
© The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.