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exact.n - Exact Samples Sizes and Inference for Clinical Trials with Binary Endpoint

Allows the user to determine minimum sample sizes that achieve target size and power at a specified alternative. For more information, see “Exact samples sizes for clinical trials subject to size and power constraints” by Lloyd, C.J. (2022) Preprint <doi:10.13140/RG.2.2.11828.94085>.

Last updated 1 years ago

1.70 score 201 downloads

CLAST - Exact Confidence Limits after a Sequential Trial

The user first provides design vectors n, a and b as well as null (p0) and alternative (p1) benchmark values for the probability of success. The key function "mv.plots.SM()" calculates mean values of exact upper and lower limits based on four different rank ordering methods. These plots form the basis of selecting a rank ordering. The function "inference()" calculates exact limits from a provided realisation and ordering choice. For more information, see "Exact confidence limits after a group sequential single arm binary trial" by Lloyd, C.J. (2020), Statistics in Medicine, Volume 38, 2389-2399, <doi:10.1002/sim.8909>.

Last updated 3 years ago

1.00 score 256 downloads