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CRiSM Seminar - Beatrijs Moerkerke

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Location: A1.01

Beatrijs Moerkerke (Ghent University, Belgium)

Estimation of controlled direct effects in the presence of exposure-induced confounding and latent variables

Estimation of the direct effect of an exposure on an outcome requires adjustment for confounders of the exposure-induced and mediator-outcome relationships. When some of these confounders are affected by the exposure, standard regression adjustment is prone to possibly severe bias. The use of inverse probability weighting has recently been suggested as a solution in the psychological literature. In this presentation, we present G-estimation as an alternative. We show that this estimation method can be easily embedded within the structural equation modeling framework and may in particular be used for estimating direct effects in the presence of latent variables. By avoiding inverse probability weighting, it accommodates the problem of unstable weights. We illustrate the approach both by simulations and by the analysis of an empirical study on the basis of which we explore the effect of age on negativity that is not mediated by mindfulness.

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