Combining nonexchangeable functional or survival data sources in oncology using generalized mixture commensurate priors

DOI10.1214/15-AOAS840zbMath1454.62368arXiv1511.05367WikidataQ31021410 ScholiaQ31021410MaRDI QIDQ902932

Bradley P. Carlin, Thomas A. Murray, Brian P. Hobbs

Publication date: 4 January 2016

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1511.05367

zbMATH Keywords

proportional hazardsclinical trialssemiparametric methodscolorectal cancerBayesian hierarchical modelmixture priorspenalized splinesevidence synthesiscommensurate priorcomputed tomographic imaging

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)

Related Items (2)

Robust adaptive incorporation of historical control data in a randomized trial of external cooling to treat septic shock ⋮ Bridging randomized controlled trials and single-arm trials using commensurate priors in arm-based network meta-analysis

Uses Software

• WinBUGS
• SemiPar
• ConfBands

Cites Work

• A comparison of regression spline smoothing procedures
• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
• Commensurate priors for incorporating historical information in clinical trials using general and generalized linear models
• Hierarchical Commensurate and Power Prior Models for Adaptive Incorporation of Historical Information in Clinical Trials
• Semiparametric Regression
• Bayesian Measures of Model Complexity and Fit
• Semiparametric Bayesian commensurate survival model for post‐market medical device surveillance with non‐exchangeable historical data
• Simultaneous Confidence Bands for Penalized Spline Estimators
• Bayesian survival analysis
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• Unnamed Item

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