gformula: Estimating causal effects in the presence of time-varying confounding or mediation using the g-computation formula
Rhian M. Daniel
Centre for Statistical Methodology
London School of Hygiene and Tropical Medicine
London, UK
[email protected]
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Bianca L. De Stavola
Centre for Statistical Methodology
London School of Hygiene and Tropical Medicine
London, UK
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Simon N. Cousens
Centre for Statistical Methodology
London School of Hygiene and Tropical Medicine
London, UK
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Abstract. This article describes a new command, gformula, that is an implementation
of the g-computation procedure. It is used to estimate the causal effect of
time-varying exposures on an outcome in the presence of time-varying confounders
that are themselves also affected by the exposures. The procedure also addresses
the related problem of estimating direct and indirect effects when the causal effect
of the exposures on an outcome is mediated by intermediate variables, and
in particular when confounders of the mediator–outcome relationships are themselves
affected by the exposures. A brief overview of the theory and a description
of the command and its options are given, and illustrations using two simulated
examples are provided.
View all articles by these authors:
Rhian M. Daniel, Bianca L. De Stavola, Simon N. Cousens
View all articles with these keywords:
gformula, causal inference, g-computation formula, time-vary-ing confounding, mediation, direct and indirect effects
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