Bayesian network meta-regression models for multivariate aggregate responses with partially observed or completely missing within-treatment sample covariance matrices
- DOI
- 10.1093/biomtc/ujag144
- Published
- 2026-07-01
- Container
- Biometrics
- Publisher
- Oxford University Press (OUP)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1093/biomtc/ujag144,
title = {Bayesian network meta-regression models for multivariate aggregate responses with partially observed or completely missing within-treatment sample covariance matrices},
author = {Simiao Gao and Sungduk Kim and Ming-Hui Chen and Arvind K Shah and Jianxin Lin and Joseph G Ibrahim},
year = {2026},
journal = {Biometrics},
doi = {10.1093/biomtc/ujag144},
url = {https://doi.org/10.1093/biomtc/ujag144}
}RIS
TY - JOUR TI - Bayesian network meta-regression models for multivariate aggregate responses with partially observed or completely missing within-treatment sample covariance matrices AU - Simiao Gao AU - Sungduk Kim AU - Ming-Hui Chen AU - Arvind K Shah AU - Jianxin Lin AU - Joseph G Ibrahim PY - 2026 JO - Biometrics DO - 10.1093/biomtc/ujag144 UR - https://doi.org/10.1093/biomtc/ujag144 ER -
APA
Gao, S., Kim, S., Chen, M., Shah, A. K., Lin, J., & Ibrahim, J. G. (2026). Bayesian network meta-regression models for multivariate aggregate responses with partially observed or completely missing within-treatment sample covariance matrices. Biometrics. https://doi.org/10.1093/biomtc/ujag144
Source records
- crossref · retrieved 2026-09-25T14:59:53.254Z