A Bayesian multivariate hierarchical model for developing a treatment benefit index using mixed types of outcomes
The study jointly models mixed types of outcomes in the context of developing ITRs. By considering multiple health outcomes, the proposed approach can advance the development of more effective and reliable personalized treatment.
Authors
- Keith Goldfeld (ORCID: https://orcid.org/0000-0002-0292-8780)
- Danni Wu (ORCID: https://orcid.org/0000-0001-6057-0804)
- Eva Petkova (ORCID: https://orcid.org/0000-0001-5129-9442)
- Hyung Park (ORCID: https://orcid.org/0000-0002-8994-9583)
Institutions
- Cancer Research And Biostatistics (US)
- New York University (US)
Publication Details
- Journal
- BMC Medical Research Methodology
- Published
- 2024-09-27
- DOI
- https://doi.org/10.1186/s12874-024-02333-z
- Citations
- 1
- Primary Topic
- Advanced Causal Inference Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.71
Funders
- National Institutes of Health
- National Institute of Mental Health
- National Center for Advancing Translational Sciences