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A Framework for Bayesian Nonparametric Inference for Causal effects of Mediation

We propose a Bayesian non-parametric (BNP) framework for estimating causal effects of mediation, the natural direct and indirect effects. The strategy is to do this in two parts. Part 1 is a flexible model (using BNP) for the observed data distribution. Part 2 is a set of uncheckable assumptions wit...

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Detalhes bibliográficos
Publicado no:Biometrics
Main Authors: Kim, Chanmin, Daniels, Michael J., Marcus, Bess H., Roy, Jason A.
Formato: Artigo
Idioma:Inglês
Publicado em: 2016
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC5288310/
https://ncbi.nlm.nih.gov/pubmed/27479682
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/biom.12575
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