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references.bib
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@book{Spiegelhalter2003,
author = {David J. Spiegelhalter and Keith R. Abrams and Jonathan P. Myles},
doi = {10.1002/0470092602},
isbn = {9780471499756},
month = {12},
publisher = {Wiley},
title = {Bayesian Approaches to Clinical Trials and Health‐Care Evaluation},
year = {2003},
}
@book{Grieve2022,
author = {Andrew P. Grieve},
city = {Boca Raton},
doi = {10.1201/9781003218531},
isbn = {9781003218531},
month = {4},
publisher = {Chapman and Hall/CRC},
title = {Hybrid Frequentist/Bayesian Power and Bayesian Power in Planning Clinical Trials},
year = {2022},
}
@book{Gelman2013,
author = {Andrew Gelman and John B. Carlin and Hal S. Stern and David B. Dunson and Aki Vehtari and Donald B. Rubin},
doi = {10.1201/b16018},
isbn = {9780429113079},
month = {11},
publisher = {Chapman and Hall/CRC},
title = {Bayesian Data Analysis},
year = {2013},
}
@article{Lee2008,
abstract = {<p>Background Two- or three-stage designs are commonly used in phase II cancer clinical trials. These designs possess good frequentist properties and allow early termination of the trial when the interim data indicate that the experimental regimen is inefficacious. The rigid study design, however, can be difficult to follow exactly because the response has to be evaluated at prespecified fixed number of patients.</p>},
author = {J Jack Lee and Diane D Liu},
doi = {10.1177/1740774508089279},
issn = {1740-7745},
issue = {2},
journal = {Clinical Trials},
month = {4},
pages = {93-106},
title = {A predictive probability design for phase II cancer clinical trials},
volume = {5},
year = {2008},
}
@article{Sambucini2021,
author = {Valeria Sambucini},
doi = {10.1007/s10260-020-00537-3},
issn = {1618-2510},
issue = {2},
journal = {Statistical Methods & Applications},
month = {6},
pages = {637-663},
title = {Efficacy and toxicity monitoring via Bayesian predictive probabilities in phase II clinical trials},
volume = {30},
year = {2021},
}