Causal Mediation Analysis in Multisite Trials

Multisite causal mediation analysis using the methods proposed by Qin and Hong (2017) and Qin, Hong, Deutsch, and Bein (2019) . It enables causal mediation analysis in multisite trials, in which individuals are assigned to a treatment or a control group at each site. It allows for estimation and hypothesis testing for not only the population average but also the between-site variance of direct and indirect effects. This strategy conveniently relaxes the assumption of no treatment-by-mediator interaction while greatly simplifying the outcome model specification without invoking strong distributional assumptions. This package also provides a function that can further incorporate a sample weight and a nonresponse weight for multisite causal mediation analysis in the presence of complex sample and survey designs and non-random nonresponse, to enhance both the internal validity and external validity. Because the identification assumptions are not always warranted, the package also provides a weighting-based balance checking function for assessing the remaining overt bias, as well as a weighting-based sensitivity analysis function for further evaluating the potential bias related to omitted confounding or to propensity score model misspecification.


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0.0.3 by Xu Qin, a year ago

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Authors: Xu Qin , Guanglei Hong , Jonah Deutsch , and Edward Bein

Documentation:   PDF Manual  

GPL-2 license

Depends on lme4, statmod, psych, MASS, ggplot2

See at CRAN