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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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| Gepubliceerd in: | Biometrics |
|---|---|
| Hoofdauteurs: | , , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
2016
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| Onderwerpen: | |
| Online toegang: | 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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