Description Usage Arguments Value References See Also Examples
Design of non-binding futility looks at multiple information times based on conditional power (CP), predictive power (PP), or condition power under current estimate (CPd) (Gallo, Mao, and Shih, 2014).
1 2 3 4 5 6 7 8 9 10 11 |
alpha |
Type I error. |
beta |
Type II error (1 - power). |
t |
A numeric vector of information times in (0, 1) for futility looks. |
gamma |
A numeric vector of probabilities (whose meaning depends on
|
side |
|
increment |
Error for the numerical solution of the sample size inflation factor. |
si |
|
scale |
Character string specifying the scaled used: |
seed |
Seed number for the randomized evaluation of multivariate normal distribution. |
An object of class fut
with the following components.
gamma1
: conditional power at information times t
converted from
the supplied gamma
and scale
;
theta
: local alternative associated with the actual power when the
futility rules of enforced;
IF
: sample size inflation factor if si
=1;
loss
: power loss if si
=0.
Gallo, P., Mao, L., and Shih, V.H. (2014). Alternative views on setting clinical trial futility criteria. Journal of Biopharmaceutical Statistics, 24, 976-993.
print.fut
, summary.fut
, plot.fut
,
powerplot
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | ## load the package
library(grpseq)
## two-sided level 0.05 test with 80% power;
## evenly spaced three futility looks with predictive power 20%;
## inflate sample size to recoup power.
obj1 <- fut(alpha=0.05,beta=0.2,t=(1:3)/4,gamma=0.2*rep(1,3),side=2,scale="PP",si=1)
obj1
## print the summary results
summary(obj1)
## do the same thing without sample size inflation
obj2 <- fut(alpha=0.05,beta=0.2,t=(1:3)/4,gamma=0.2*rep(1,3),side=2,scale="PP",si=0)
obj2
## print the summary results
summary(obj2)
oldpar <- par(mfrow = par("mfrow"))
par(mfrow=c(1,2))
## plot the futility boundaries by z-value
plot(obj2,scale='z',lwd=2,main="")
## plot the futility boundaries by B-value
plot(obj2,scale='b',lwd=2,main="")
par(oldpar)
## plot the power curve as a function of the (local)
## effect size in units of the hypothesized effect size
## ref=TRUE requests the power curve for the original one-time analysis
powerplot(obj2,lwd=2, ref=TRUE)
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