Dear Workshop Community,
Our next meeting will be *Wednesday October 23*, where Xiang Zhou will
present research on* "**Effect Decomposition in the Presence of
Treatment-induced Confounding: A Regression-with-Residuals Approach"*.
*Abstract:* Analyses of causal mediation are often complicated by
treatment-induced confounders of the mediator-outcome relationship. In the
presence of such confounders, the natural direct and indirect effects of
treatment on the outcome, into which the total effect can be additively
decomposed, are not identified. An alternative but similar set of effects,
known as randomized intervention analogues to the natural direct effect
(R-NDE) and the natural indirect effect (R-NIE), can still be identified in
this situation, but existing estimators for these effects require a
complicated weighting procedure that is difficult to use in practice. We
introduce a new method for estimating the R-NDE and R-NIE that involves
only a minor adaptation of the comparatively simple regression methods used
to perform effect decomposition in the absence of treatment-induced
confounding. It involves fitting (a) a generalized linear model for the
conditional mean of the mediator given treatment and a set of baseline
confounders and (b) a linear model for the conditional mean of the outcome
given the treatment, mediator, baseline confounders, and a set of
treatment-induced confounders that have been residualized with respect to
the observed past. The R-NDE and R-NIE are simple functions of the
parameters in these models when they are correctly specified and when there
are no unobserved variables that confound the treatment-outcome,
treatment-mediator, or mediator-outcome relationships. We illustrate the
method by decomposing the effect of education on depression at midlife into
components operating through income versus alternative factors. R and Stata
packages are available for implementing the proposed method.
*Where:* CGIS Knafel Building, Room K354 (see this link
<https://map.harvard.edu/?bld=04471&level=9> for directions).
*When: *Wednesday, October 23 at 12 noon - 1:30 pm.
All are welcome. Lunch will be provided.
Best,
Georgie
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