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. ----- 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). ----- 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. ----- 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) ----- 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. ----- Contains further functions for power calculations / sample size estimation for dose proportionality studies using the Power model.
|Author||Detlew Labes [aut, cre], Helmut Schuetz [aut], Benjamin Lang [aut]|
|Date of publication||2018-04-12 19:43:08 UTC|
|Maintainer||Detlew Labes <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.