Epgo_bias_normal | R Documentation |
In the case we do not only want do discount for overoptimistic results in phase II when calculating the sample size in phase III,
but also when deciding whether to go to phase III or not the functions Epgo_normal_L2
and Epgo_normal_R2
are necessary.
The function Epgo_normal_L2
uses an additive adjustment parameter (i.e. adjust the lower bound of the one-sided confidence interval),
the function Epgo_normal_R2
uses a multiplicative adjustment parameter (i.e. use estimate with a retention factor)
Epgo_normal_L2(kappa, n2, Adj, w, Delta1, Delta2, in1, in2, a, b, fixed)
Epgo_normal_R2(kappa, n2, Adj, w, Delta1, Delta2, in1, in2, a, b, fixed)
kappa |
threshold value for the go/no-go decision rule |
n2 |
total sample size for phase II; must be even number |
Adj |
adjustment parameter |
w |
weight for mixture prior distribution |
Delta1 |
assumed true treatment effect for standardized difference in means |
Delta2 |
assumed true treatment effect for standardized difference in means |
in1 |
amount of information for |
in2 |
amount of information for |
a |
lower boundary for the truncation |
b |
upper boundary for the truncation |
fixed |
choose if true treatment effects are fixed or random, if TRUE |
The output of the functions Epgo_normal_L2
and Epgo_normal_R2
is the expected number of participants in phase III with conservative decision rule and sample size calculation.
res <- Epgo_normal_L2(kappa = 0.1, n2 = 50, Adj = 0, w = 0.3,
Delta1 = 0.375, Delta2 = 0.625, in1 = 300, in2 = 600,
a = 0.25, b = 0.75, fixed = FALSE)
res <- Epgo_normal_R2(kappa = 0.1, n2 = 50, Adj = 1, w = 0.3,
Delta1 = 0.375, Delta2 = 0.625, in1 = 300, in2 = 600,
a = 0.25, b = 0.75, fixed = FALSE)
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