Power2Stage: Power and Sample-Size Distribution of 2-Stage Bioequivalence
Functions to obtain the operational characteristics of
bioequivalence studies with 2-stage designs via simulations
- Contains a function to calculate power and sample-size distribution
of 2-stage bioequivalence (BE) studies with a 2x2 crossover design
according to Potvin et al. / Montague et al. modified to include a
futility Nmax and modified to do the sample size estimation step
with PE and mse of stage 1.
- Contains further a function with the modifications according to
Karalis & Macheras which use both point estimate (PE) and mse from stage 1
also for the power monitoring steps.
- The third function power.2stage.fC() calculates power and sample-size
distribution of 2-stage BE studies with a futility criterion
for the PE or CI of T/R from stage 1.
- The fourth function power.2stage.GS() calculates power of non-adaptive
group sequential (2-stage) BE studies.
- The fifth function power.2stage.p() calculates power and sample size
distribution of 2-stage BE studies with 2 parallel groups.
This function has a sibling power.2stage.pAF(), which performs exactly as
described in A.Fuglsang 2014
- Another function power.2stage.ssr() allows the power calculation
for 2-stage studies with (blinded) interim sample size re-estimation.
||PowerTOST, stats, mvtnorm
||Detlew Labes [aut, cre],
Helmut Schuetz [ctb]
||Detlew Labes <DetlewLabes at gmx.de>
||GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]