Bayesian identification of structural coefficients in causal models and the causal false-positive risk of confounders and colliders in linear Markovian models

BACKGROUND: Causal inference has seen an increasing popularity in medical research. Estimation of causal effects from observational data allows to draw conclusions from data when randomized controlled trials cannot be conducted. Although the identification of structural causal models (SCM) and the c...

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Detalles Bibliográficos
Autor principal: Kelter, Riko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8883695/
https://www.ncbi.nlm.nih.gov/pubmed/35220960
http://dx.doi.org/10.1186/s12874-021-01473-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8883695/
https://www.ncbi.nlm.nih.gov/pubmed/35220960
http://dx.doi.org/10.1186/s12874-021-01473-w

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