Package index • PowerTOST

All functions
`CI.BE()`	1–2*alpha confidence interval given point estimate, CV, and n
`CI.RatioF()`	1–2*alpha Fieller CI given point estimate, CV (, CVb) and n
`CV2se()` `se2CV()` `CV2mse()` `mse2CV()`	Helper functions
`CVCL()`	Confidence limits of a CV for log-normal data
`CVfromCI()` `CI2CV()`	CV from a given Confidence interval
`CVp2CV()`	Decompose CV(T) and CV(R) from 'pooled' CV of T/R
`CVpooled()` `print(<CVp>)`	Pooled CV from several studies
`CVwRfromU()` `U2CVwR()`	CVwR from the upper expanded limit (ABEL)
`OwensQ()`	Owen's Q-function
`OwensQOwen()`	Owen's Q-function via repeated integration by parts
`OwensT()`	Owen's T-function
`bib.CL()`	Design matrices of period balanced incomplete block designs
`data2x2` `ct5.1` `ct5.2` `ct5.3` `ct5.4.1`	Sample Size Tables for the Classical 2x2 Crossover Design
`data2x2x3` `ct9.6.2` `ct9.6.6`	Sample Size Tables for the 2x2x3 Replicate Crossover Design
`data2x4x4` `ct9.6.4` `ct9.6.8`	Sample Size Tables for the 2x4x4 Replicate Crossover Design
`data_parallel` `ctSJ.VIII.10` `ctSJ.VIII.20` `ctCW.III`	Sample Size Tables for the Parallel Group Design
`defunct`	Removed functions in PowerTOST
`deprecated`	Deprecated functions in PowerTOST
`exppower.TOST()`	Expected power of the TOST procedure
`exppower.noninf()`	Expected power of the non-inferiority test
`expsampleN.TOST()`	Sample size based on expected power
`expsampleN.noninf()`	Sample size based on expected power for the non-inferiority test
`known.designs()`	Show the 'known' designs
`pa.ABE()` `print(<pwrA>)` `plot(<pwrA>)`	Power analysis for average bioequivalence (ABE)
`pa.NTID()`	Power analysis for scaled ABE for NTIDs
`pa.scABE()`	Power analysis for scaled average bioequivalence (scABE)
`power.2TOST()`	Power for two simultaneous TOST procedures
`power.HVNTID()`	(Empirical) Power for BE decision via FDA method for highly variable NTIDs
`power.NTID()`	(Empirical) Power for BE decision via FDA method for NTIDs
`power.RSABE()`	(Empirical) Power for BE decision via linearized scaled ABE criterion
`power.RSABE2L.sdsims()`	(Empirical) Power of BE Decision via Reference Scaled ABE
`power.RatioF()`	Power for equivalence of the ratio of two means with normality on original scale
`power.TOST()`	Power of the classical TOST procedure
`power.TOST.sds()`	Power calculation of the BE decision with models incorporating groups
`power.TOST.sim()`	Power of the TOST procedure obtained via simulations
`power.dp()`	Power of dose-proportionality studies evaluated via Power model
`power.noninf()`	Power of the one-sided non-inferiority t-test
`power.scABEL()`	(Empirical) Power of BE decision via scaled (widened) BE acceptance limits
`power.scABEL.sdsims()`	(Empirical) Power of BE decision via scaled (widened) BE acceptance limits
`pvalue.TOST()` `pvalues.TOST()`	p-value(s) of the TOST procedure
`reg_const()`	Constructor of an object with class 'regSet' containing the regulatory settings for ABEL
`sampleN.2TOST()`	Sample size based on power of two TOSTs
`sampleN.HVNTID()`	Sample size estimation for BE decision via FDA method for highly variable (HV) narrow therapeutic index drugs (NTIDs)
`sampleN.NTID()`	Sample size estimation for BE decision via the FDA's method for narrow therapeutic index drugs (NTIDs)
`sampleN.RSABE()`	Sample size estimation for BE decision via linearized scaled ABE criterion
`sampleN.RSABE2L.sdsims()`	Sample size estimation for BE Decision via Reference Scaled ABE
`sampleN.RatioF()`	Sample size for equivalence of the ratio of two means with normality on original scale
`sampleN.TOST()`	Sample size based on power of TOST
`sampleN.dp()`	Sample size estimation of dose-proportionality studies evaluated via the power model
`sampleN.noninf()`	Sample size for the non-inferiority t-test
`sampleN.scABEL()`	Sample size estimation for BE decision via scaled (expanded) BE acceptance limits
`sampleN.scABEL.ad()`	Sample size estimation for ABEL and iteratively adjusted alpha
`sampleN.scABEL.sdsims()`	Sample size estimation for BE decision via scaled (expanded) BE acceptance limits
`scABEL()`	Scaled (widened) BE Acceptance Limits
`scABEL.ad()`	Iteratively adjusted alpha for ABEL
`type1error.2TOST`	Type I error rate for two simultaneous TOST procedures

Reference

All functions