A study of the probit model with latent variables in Phase I clinical trials
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Publication:5220814
DOI10.1080/00949655.2014.885976zbMath1457.62365OpenAlexW1990315220MaRDI QIDQ5220814
Keying Ye, Yan-Ping Wang, Xiao-Bin Yang
Publication date: 27 March 2020
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949655.2014.885976
Markov chain Monte CarloBayesian methodprobit modellatent variablephase I clinical trialcontinual reassessment methoddose finding
Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)
Related Items (1)
Cites Work
- Continual Reassessment Method: A Practical Design for Phase 1 Clinical Trials in Cancer
- Dose Finding for Continuous and Ordinal Outcomes with a Monotone Objective Function: A Unified Approach
- Bayesian analysis of dichotomous quantal response models
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- Two-dimensional toxic dose and multivariate logistic regression, with application to decompression sickness
- Sampling-Based Approaches to Calculating Marginal Densities
- On the multivariate predictive distribution of multi-dimensional effective dose: a Bayesian approach
- Consistency of continual reassessment method under model misspecification
- Bayesian Analysis of Binary and Polychotomous Response Data
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