bib.CL

This function returns the 'design' matrix of incomplete block designs described
in Chow & Liu's book. The design matrices where recoded 1=R, 2=T1, 3=T2 ...

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.
    -----
    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.
    -----
    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 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.    

bib.CL: Design matrices of period balanced incomplete block designs

Description

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Examples