This function performs the sample size estimation for the BE decision via
the FDA’s method for highly variable NTIDs as described in respective guidances based on simulations.
The study designs may be the full replicate design 2x2x4 with 4 periods (TRTR|RTRT) and
the 3-period replicate design 2x2x3 with sequences RTR|TRT.
sampleN.HVNTID(alpha = 0.05, targetpower = 0.8, theta0, theta1, theta2, CV,
design = c("2x2x4", "2x2x3"), nsims = 1e+05, nstart, imax = 100,
print = TRUE, details = TRUE, setseed = TRUE)Returns a data.frame with the input and sample size results.
The Sample size column contains the total sample size.
The nlast column contains the last n value. May be useful for re-starting.
Type I error probability. Per convention mostly set to 0.05.
Power to achieve at least. Must be >0 and <1.
Typical values are 0.8 or 0.9.
‘True’ or assumed T/R ratio.
Defaults to 0.95 if not given explicitly.
Conventional lower ABE limit to be applied in the FDA procedure.
Defaults to 0.8 if not given explicitly.
Conventional upper ABE limit to be applied in the FDA procedure.
Defaults to 1.25 if not given explicitly.
Intra-subject coefficient(s) of variation as ratio (not percent).
If given as a scalar (length(CV)==1) the same CV of Test
and Reference is assumed (homoscedasticity, CVwT==CVwR).
If given as a vector (length(CV)==2), i.e., assuming
heteroscedasticity, the CV of the Test must be given in CV[1] and the one of the Reference in the CV[2].
Design of the study to be planned.
"2x2x4" is the full replicate with 2 sequences and 4 periods (TRTR|RTRT).
"2x2x3" is the full replicate with 2 sequences and 3 periods (TRT|RTR).
Defaults to design="2x2x4".
Number of simulations to be performed to obtain the empirical power. Defaults to 100,000 = 1e+5.
Set this to a start value for the sample size if a previous run failed.
May be missing.
Maximum number of steps in sample size search. Defaults to 100.
If TRUE (default) the function prints its results. If FALSE only the resulting dataframe will be returned.
If set to TRUE, the default, the steps during sample size search are shown.
Moreover the details of the method settings are printed.
Simulations are dependent on the starting point of the (pseudo) random number
generator. To avoid differences in power values for different runs a
set.seed(123456) is issued if setseed=TRUE, the default.
D. Labes
For some input constellations the sample size search may be very time
consuming and will eventually also fail since the start values chosen may
not really reasonable for them.
In case of a failed sample size search you may restart with setting the argument
nstart.
For deciding BE the study must pass the conventional ABE test and additionally
the test that the ratio of sWT/sWR is <= 2.5.
The simulations are done via the distributional properties of the statistical
quantities necessary for deciding BE based on these method.
Details can be found in a document Implementation_scaledABE_sims located in
the /doc sub-directory of the package.
The estimated sample size gives always the total number of subjects (not subject/sequence -- like in some other software packages).
Food and Drug Administration, Office of Generic Drugs (OGD). Draft Guidance on Dabigatran Etexilate Mesylate. Recommended Jun 2012; Revised Sep 2015, Jul 2017. download
Food and Drug Administration, Office of Generic Drugs (OGD). Draft Guidance on Rivaroxaban. Recommended Sep 2015. download
Food and Drug Administration, Office of Generic Drugs (OGD). Draft Guidance on Edoxaban Tosylate. Recommended May 2017; Revised Mar 2020. download
power.HVNTID
and power.NTIDFDA, sampleN.NTIDFDA for NTIDs with
low variability
# using all defaults but CV
sampleN.HVNTID(CV = 0.3)
# should give
# n=22 with an (empirical) power of 0.829700
# Test formulation with lower variability but same pooled CV
CVs <- CVp2CV(0.3, ratio = 0.25)
sampleN.HVNTID(CV = CVs)
# should give (no distinct difference to example above)
# n=22 with an (empirical) power of 0.837520
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