Helmut
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2019-06-14 18:01

Posting: # 20326
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 package replicateBE on CRAN [R for BE/BA]

[image]Dear all,

package replicateBE is on CRAN. Background information in its Vignette.

Data can be imported from CSV- or XLS(X)-files. Following ten designs are covered:
  • Four period full replicates
    • TRTR | RTRT
    • TRRT | RTTR
    • TTRR | RRTT
    • TRTR | RTRT | TRRT | RTTR 1
    • TRRT | RTTR | TTRR | RRTT 1
  • Two period full replicate
    • TR | RT | TT | RR 2
  • Three period full replicates
    • TRT | RTR
    • TRR | RTT
  • Three period partial replicates
    • TRR | RTR | RRT
    • TRR | RTR 3
Implemented:
  • Estimation of CVwR (and CVwT in full replicates)
    A linear model of log-transformed PK responses and effects
       sequence, subject(sequence), period
    of the reference (and test, if possible) treatment – where all effects are fixed (i.e., ANOVA).
    Estimated via function lm() of library stats.
    In full replicate designs assessment of \(s_{wT}/s_{wR}\) and the upper confidence limit of \(\sigma_{wT}/\sigma_{wR}\) for the WHO’s reference-scaling of AUC.

  • Method A
    A linear model of log-transformed PK responses and effects
       sequence, subject(sequence), period, treatment
    – where all effects are fixed (i.e., ANOVA).
    Estimated via function lm() of library stats.

  • Method B
    A linear mixed model of log-transformed PK responses and effects
       sequence, subject(sequence), period, treatment
    – where subject(sequence) is a random effect and all others are fixed.
    Three options
    1. Estimated via function lme() of library nlme. Uses degrees of freedom equivalent to SAS’ DDFM=CONTAIN and Phoenix/WinNonlin’s DF Residual. Implicitly preferred according to the EMA’s Q&A document and hence, the default.
    2. Estimated via function lmer() of library lmerTest. Uses Satterthwaite’s degrees of freedom equivalent to SAS’ DDFM=SATTERTHWAITE and Phoenix/WinNonlin’s DF Satterthwaite. This is the only option available in SPSS.
      Potentially better for highly incomplete data.
    3. Estimated via function lmer() of library lmerTest. Uses the Kenward-Roger approximation equivalent to SAS’ DDFM=KENWARDROGER. This is the only option available in JMP.
      Potentially better for highly incomplete data.
  • ABE
    Conventional Average Bioequivalence. Optionally with tighter (EMA: NTIDs) or wider limits (GCC: Cmax).
Assessment of potential outliers in the ABEL-methods is done by box plots of studentized model residuals.

Installation/Update of the latest release from CRAN with

install.packages("replicateBE", repos = "https://cloud.r-project.org/")

Installation of the development version from GitHub:

devtools::install_github("Helmut01/replicateBE")


Enjoy!

Bug reports to GitHub or the maintainer.


  1. Confounded effects (design not recommended).
  2. Balaam’s design (not recommended due to poor power characteristics).
  3. Extra-reference design; biased in the presence of period effects (design not recommended).

Cheers,
Helmut Schütz
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