Package: baskexact 1.0.2

baskexact: Analytical Calculation of Basket Trial Operating Characteristics

Analytically calculates the operating characteristics of single-stage and two-stage basket trials with equal sample sizes using the power prior design by Baumann et al. (2024) <doi:10.48550/arXiv.2309.06988> and the design by Fujikawa et al. (2020) <doi:10.1002/bimj.201800404>.

Authors:Lukas Baumann [aut, cre]

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baskexact/json (API)

# Install 'baskexact' in R:
install.packages('baskexact', repos = c('https://lbau7.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/lbau7/baskexact/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

24 exports 2 stars 1.82 score 43 dependencies 11 scripts 372 downloads

Last updated 1 months agofrom:a524dd9714. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 14 2024
R-4.5-win-x86_64NOTESep 14 2024
R-4.5-linux-x86_64NOTESep 14 2024
R-4.4-win-x86_64NOTESep 14 2024
R-4.4-mac-x86_64NOTESep 14 2024
R-4.4-mac-aarch64NOTESep 14 2024
R-4.3-win-x86_64NOTESep 14 2024
R-4.3-mac-x86_64NOTESep 14 2024
R-4.3-mac-aarch64NOTESep 14 2024

Exports:adjust_lambdabasket_testcheck_mon_betweencheck_mon_withinecdessestimget_scenariosglobalweights_diffglobalweights_fixinterim_posteriorinterim_postpredopt_designplot_weightspowsetupOneStageBasketsetupTwoStageBaskettoerweights_cppweights_fujikawaweights_jsdweights_mmlweights_poolweights_separate

Dependencies:arrangementsclicodetoolscolorspacedigestdoFutureextraDistrfansifarverforeachfuturefuture.applyggplot2globalsgluegmpgtableisobanditeratorslabelinglatticelifecyclelistenvmagrittrMASSMatrixmgcvmunsellnlmeparallellypillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangscalestibbleutf8vctrsviridisLitewithr

Extending baskexact

Rendered fromv2_Extending_baskexact.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2024-03-13
Started: 2024-03-13

Introduction to baskexact

Rendered fromv1_Introduction.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2024-05-23
Started: 2024-03-13

Reproduce Results From Fujikawa et al. (2020)

Rendered fromv3_Reproduce_Fujikawa.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2024-03-13
Started: 2024-03-13

Readme and manuals

Help Manual

Help pageTopics
Adjust Lambdaadjust_lambda adjust_lambda,OneStageBasket-method adjust_lambda,TwoStageBasket-method
Test for the Results of a Basket Trialbasket_test basket_test,OneStageBasket-method
Check Between-Trial Monotonicitycheck_mon_between check_mon_between,OneStageBasket-method
Check Within-Trial Monotonicitycheck_mon_within check_mon_within,OneStageBasket-method
Expected number of correct decisionsecd ecd,OneStageBasket-method ecd,TwoStageBasket-method
Expected Sample Sizeess ess,TwoStageBasket-method
Posterior Mean and Mean Squared Errorestim estim,OneStageBasket-method estim,TwoStageBasket-method
Create a Scenario Matrixget_scenarios
Global Weights Based on Response Rate Differencesglobalweights_diff
Fixed Global Weightsglobalweights_fix
Interim analysis based on the posterior probabilityinterim_posterior interim_posterior,TwoStageBasket-method
Interim analysis based on the posterior predictive probabilityinterim_postpred interim_postpred,TwoStageBasket-method
Class OneStageBasketOneStageBasket OneStageBasket-class
Optimize a Basket Designopt_design opt_design,OneStageBasket-method opt_design,TwoStageBasket-method
Plot Weight Functionsplot_weights plot_weights,OneStageBasket-method
Powerpow pow,OneStageBasket-method pow,TwoStageBasket-method
Setup OneStageBasketsetupOneStageBasket
Setup TwoStageBasketsetupTwoStageBasket
Type 1 Error Ratetoer toer,OneStageBasket-method toer,TwoStageBasket-method
Class TwoStageBasketTwoStageBasket TwoStageBasket-class
Weights Based on the Calibrated Power Priorweights_cpp weights_cpp,OneStageBasket-method weights_cpp,TwoStageBasket-method
Weights Based on Fujikawa et al.'s Designweights_fujikawa weights_fujikawa,OneStageBasket-method weights_fujikawa,TwoStageBasket-method
Weights Based on the Jensen-Shannon Divergenceweights_jsd weights_jsd,OneStageBasket-method weights_jsd,TwoStageBasket-method
Weights Based on the Marginal Maximum Likelihoodweights_mml weights_mml,OneStageBasket-method weights_mml,TwoStageBasket-method
Pooled Analysisweights_pool weights_pool,OneStageBasket-method weights_pool,TwoStageBasket-method
Separate Analysis in Each Basketweights_separate weights_separate,OneStageBasket-method weights_separate,TwoStageBasket-method