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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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| Publicat a: | Biometrics |
|---|---|
| Autors principals: | , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2016
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| Matèries: | |
| Accés en línia: | 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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