BEAST: Bayesian hybrid design with flexible sample size adaptation for time-to-event endpoints
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Publication:6560579
DOI10.1002/sim.9936zbMath1540.62148MaRDI QIDQ6560579
Jianchang Lin, Rachael Liu, Dehua Bi, Meizi Liu
Publication date: 23 June 2024
Published in: Statistics in Medicine (Search for Journal in Brave)
real-world datahistorical controlhybrid designBayesian borrowingsample size rebalancesemiparametric meta-analytic-predictive prior
Cites Work
- On the half-Cauchy prior for a global scale parameter
- Hierarchical Commensurate and Power Prior Models for Adaptive Incorporation of Historical Information in Clinical Trials
- Robust meta‐analytic‐predictive priors in clinical trials with historical control information
- Determining the Effective Sample Size of a Parametric Prior
- Predictively consistent prior effective sample sizes
- Modified power prior with multiple historical trials for binary endpoints
- Bayesian leveraging of historical control data for a clinical trial with time-to-event endpoint
- Propensity-score-based meta-analytic predictive prior for incorporating real-world and historical data
- Bayesian semiparametric prior for historical control borrowing in clinical trials
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