Epgo_bias | 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_L2
and Epgo_R2
are necessary.
The function Epgo_L2
uses an additive adjustment parameter (i.e. adjust the lower bound of the one-sided confidence interval),
the function Epgo_R2
uses a multiplicative adjustment parameter (i.e. use estimate with a retention factor)
Epgo_L2(HRgo, d2, Adj, w, hr1, hr2, id1, id2, fixed)
Epgo_R2(HRgo, d2, Adj, w, hr1, hr2, id1, id2, fixed)
HRgo |
threshold value for the go/no-go decision rule |
d2 |
total number of events for phase II; must be even number |
Adj |
adjustment parameter |
w |
weight for mixture prior distribution |
hr1 |
first assumed true treatment effect on HR scale for prior distribution |
hr2 |
second assumed true treatment effect on HR scale for prior distribution |
id1 |
amount of information for |
id2 |
amount of information for |
fixed |
choose if true treatment effects are fixed or random, if TRUE |
The output of the functions Epgo_L2
and Epgo_R2
is the expected probability to go to phase III with conservative decision rule and sample size calculation.
res <- Epgo_L2(HRgo = 0.8, d2 = 50, Adj = 0.4,
w = 0.3, hr1 = 0.69, hr2 = 0.81,
id1 = 280, id2 = 420, fixed = FALSE)
res <- Epgo_R2(HRgo = 0.8, d2 = 50, Adj = 0.9,
w = 0.3, hr1 = 0.69, hr2 = 0.81,
id1 = 280, id2 = 420, fixed = FALSE)
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