An AI-powered Bayesian Generative Modeling Approach for Causal Inference in Observational Studies.

Liu Q, Wong WH

DOI: 10.1080/01621459.2026.2654227
Published: 2026 Jun 4
Container: Journal of the American Statistical Association
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1080/01621459.2026.2654227,
  title = {An AI-powered Bayesian Generative Modeling Approach for Causal Inference in Observational Studies.},
  author = {Liu Q and Wong WH},
  year = {2026},
  journal = {Journal of the American Statistical Association},
  doi = {10.1080/01621459.2026.2654227},
  url = {https://doi.org/10.1080/01621459.2026.2654227}
}

RIS

TY  - JOUR
TI  - An AI-powered Bayesian Generative Modeling Approach for Causal Inference in Observational Studies.
AU  - Liu Q
AU  - Wong WH
PY  - 2026
JO  - Journal of the American Statistical Association
DO  - 10.1080/01621459.2026.2654227
UR  - https://doi.org/10.1080/01621459.2026.2654227
ER  -

APA

Q, L., & WH, W. (2026). An AI-powered Bayesian Generative Modeling Approach for Causal Inference in Observational Studies.. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.2026.2654227

Source records

pubmed · retrieved 2026-09-26T10:18:40.420Z