sampleN.NTIDFDA(alpha = 0.05, targetpower = 0.8, theta0, theta1, theta2, CV,
nsims = 1e+05, nstart, print = TRUE, details = TRUE,
setseed = TRUE)
length(CV) = 1
the same CV is assumed for Test and Reference.
If length(CV) = 2
the CV for Test must be given in CV[1] and for
Reference in CV[2].TRUE
(default) the function prints its results.
If FALSE
only the resulting dataframe will be returned.TRUE
, the default, the steps during sample size search are shown.
Moreover the details of the method settings are printed.set.seed(123456)
is issued if setseed=TRUE
, the default.exp(+-1.053605*swR)
.
In case of a failed sample size search you may restart with setting tha argument nstart
.
In case of theta0 values outside the implied scaled (tightened/widened) ABE limits
no sample size estimation is possible and the function throws an error
(f.i. CV=0.04, theta0=0.95).power.NTIDFDA
sampleN.NTIDFDA(CV=0.04,theta0=0.975)
# should give
# n=54 with an (empirical) power of 0.809590
#
# Test formulation with lower variability
sampleN.NTIDFDA(CV=c(0.04,0.06),theta0=0.975)
# should give
# n=20 with an (empirical) power of 0.0.814610
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