basket-package: Basket Trial Analysis
In kaneplusplus/basket: Basket Trial Analysis
basket-package R Documentation
Basket Trial Analysis
Description
The R basket package provides for the designs and analysis of
basket trials for multi-source exchangeability models (MEM)
<https://doi.org/10.1093/biostatistics/kxx031>
allowing arms to "share" power with similar arms in a trial. The package
is intended to perform the exact or MCMC computation of the operating
characteristics of different scenarios. Calculations derived from these
analyses include the posterior probabilities, HPD boundaries, effective
sample sizes (ESS), mean and median estimations can be calculated with
this package using the MEM method. Along with providing "basketwise"
analyses, the package includes similar calculations for "clusterwise"
analyses where a cluster a set of similar baskets. In addition plotting
tools are provided to visualize basket and cluster density as well as their
exchangeability. The package includes the following main functions:
[basket_name()] Get the basket names in an analysis
[basket_pep()] Get the Posterior Exchangeability Probability
(PEP) matrix for the arms in the trial.
[basket_map()] Get the Maximum A Posteriori (MAP) matrix for the
arms in a trial.
[cluster_pep()] Get the Posterior Exchangeability Probability
(PEP) matrix for the arms in the trial.
[cluster_map()] Get the Maximum A Posteriori (MAP) matrix for
the arms in a trial.
[sample_posterior()] Sample from the posterior distribution of
the arms in the trial.
[mem_exact()] Create a basket analysis using the exact method.
[mem_mcmc()] Create a basket analysis using the exact method.
[summary()] Summarize the results of an analysis.
[update_p0()] Update the null that a basket response rate is
above a specified value.
[plot_density()] Plot the estimated densities of arms or clusters.
[plot_pep()] Show the exchangeogram of the PEP matrix.
[plot_mem()] Plot the arm prior, MAP, and PEP of a basket trial.
References
Vemurafenib in multiple nonmelanoma cancers with braf v600
mutations Hyman DM, Puzanov I, Subbiah V, Faris JE, Chau I, Blay JY,
Wolf J, Raje NS, Diamond EL, Hollebecque A, et al.
New England Journal of Medicine 2015; 373(8):726–736.
<https://doi:10.1056/NEJMoa1502309>
Bayesian basket trial design with exchangeability monitoring
BP Hobbs, R Landin Statistics in medicine 37 (25), 3557-357.
<https://doi.org/10.1002/sim.7893>
Statistical challenges posed by uncontrolled master protocols:
sensitivity analysis of the vemurafenib study BP Hobbs, MJ Kane, DS Hong,
R Landin Annals of Oncology 29 (12), 2296-2301. <doi:10.1093/annonc/mdy457>
Bayesian hierarchical modeling based on multisource
exchangeability AM Kaizer, JS Koopmeiners, BP Hobbs Biostatistics 19 (2),
169-184. <https://doi.org/10.1093/biostatistics/kxx031>
kaneplusplus/basket documentation built on July 31, 2023, 6:46 p.m.
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| basket-package | R Documentation |
Basket Trial Analysis
Description
The R basket package provides for the designs and analysis of basket trials for multi-source exchangeability models (MEM) <https://doi.org/10.1093/biostatistics/kxx031> allowing arms to "share" power with similar arms in a trial. The package is intended to perform the exact or MCMC computation of the operating characteristics of different scenarios. Calculations derived from these analyses include the posterior probabilities, HPD boundaries, effective sample sizes (ESS), mean and median estimations can be calculated with this package using the MEM method. Along with providing "basketwise" analyses, the package includes similar calculations for "clusterwise" analyses where a cluster a set of similar baskets. In addition plotting tools are provided to visualize basket and cluster density as well as their exchangeability. The package includes the following main functions:
[basket_name()] Get the basket names in an analysis
[basket_pep()] Get the Posterior Exchangeability Probability (PEP) matrix for the arms in the trial.
[basket_map()] Get the Maximum A Posteriori (MAP) matrix for the arms in a trial.
[cluster_pep()] Get the Posterior Exchangeability Probability (PEP) matrix for the arms in the trial.
[cluster_map()] Get the Maximum A Posteriori (MAP) matrix for the arms in a trial.
[sample_posterior()] Sample from the posterior distribution of the arms in the trial.
[mem_exact()] Create a basket analysis using the exact method.
[mem_mcmc()] Create a basket analysis using the exact method.
[summary()] Summarize the results of an analysis.
[update_p0()] Update the null that a basket response rate is above a specified value.
[plot_density()] Plot the estimated densities of arms or clusters.
[plot_pep()] Show the exchangeogram of the PEP matrix.
[plot_mem()] Plot the arm prior, MAP, and PEP of a basket trial.
References
Vemurafenib in multiple nonmelanoma cancers with braf v600 mutations Hyman DM, Puzanov I, Subbiah V, Faris JE, Chau I, Blay JY, Wolf J, Raje NS, Diamond EL, Hollebecque A, et al. New England Journal of Medicine 2015; 373(8):726–736. <https://doi:10.1056/NEJMoa1502309>
Bayesian basket trial design with exchangeability monitoring BP Hobbs, R Landin Statistics in medicine 37 (25), 3557-357. <https://doi.org/10.1002/sim.7893>
Statistical challenges posed by uncontrolled master protocols: sensitivity analysis of the vemurafenib study BP Hobbs, MJ Kane, DS Hong, R Landin Annals of Oncology 29 (12), 2296-2301. <doi:10.1093/annonc/mdy457>
Bayesian hierarchical modeling based on multisource exchangeability AM Kaizer, JS Koopmeiners, BP Hobbs Biostatistics 19 (2), 169-184. <https://doi.org/10.1093/biostatistics/kxx031>
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