Contains functions to calculate power and sample size for
various study designs used for bioequivalence studies.
See function known.designs() for study designs covered.
Moreover the package contains functions for power and sample size
based on 'expected' power in case of uncertain (estimated) variability
and/or uncertain theta0.
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Added are functions for the power and sample size for the ratio of
two means with normally distributed data on the original scale
(based on Fieller's confidence ('fiducial') interval).
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Contains further functions for power and sample size calculations based on
non-inferiority t-test. This is not a TOST procedure but eventually useful
if the question of 'non-superiority' must be evaluated.
The power and sample size calculations based on non-inferiority test may
also performed via 'expected' power in case of uncertain (estimated)
variability and/or uncertain theta0.
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Contains functions power.scABEL() and sampleN.scABEL() to calculate power
and sample size for the BE decision via scaled (widened) BE acceptance
limits (EMA recommended) based on simulations.
Contains also functions scABEL.ad() and sampleN.scABEL.ad() to iteratively
adjust alpha in order to maintain the overall consumer risk in ABEL studies
and adapt the sample size for the loss in power.
Contains further functions power.RSABE() and sampleN.RSABE() to calculate
power and sample size for the BE decision via reference scaled ABE criterion
according to the FDA procedure based on simulations.
Contains further functions power.NTIDFDA() and sampleN.NTIDFDA() to calculate
power and sample size for the BE decision via the FDA procedure for NTID's
based on simulations.
Contains further functions power.HVNTID() and sampleN.HVNTID() to calculate
power and sample size for the BE decision via the FDA procedure for
highly variable NTID's (see FDA Dabigatran / rivaroxaban guidances)
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Contains functions for power analysis of a sample size plan for ABE
(pa.ABE()), scaled ABE (pa.scABE()) and scaled ABE for NTID's (pa.NTIDFDA())
analysing power if deviating from assumptions of the plan.
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Contains further functions for power calculations / sample size estimation
for dose proportionality studies using the Power model.