| ciapower {Hmisc} | R Documentation |
Uses the method of Peterson and George to compute the power of an
interaction test in a 2 x 2 setup in which all 4 distributions are
exponential. This will be the same as the power of the Cox model
test if assumptions hold. The test is 2-tailed.
The duration of accrual is specified
(constant accrual is assumed), as is the minimum follow-up time.
The maximum follow-up time is then accrual + tmin. Treatment
allocation is assumed to be 1:1.
ciapower(tref, n1, n2, m1c, m2c, r1, r2, accrual, tmin,
alpha=0.05, pr=TRUE)
tref |
time at which mortalities estimated |
n1 |
total sample size, stratum 1 |
n2 |
total sample size, stratum 2 |
m1c |
tref-year mortality, stratum 1 control |
m2c |
tref-year mortality, stratum 2 control |
r1 |
% reduction in m1c by intervention, stratum 1
|
r2 |
% reduction in m2c by intervention, stratum 2
|
accrual |
duration of accrual period |
tmin |
minimum follow-up time |
alpha |
type I error probability |
pr |
set to FALSE to suppress printing of details
|
power
prints
Frank Harrell
Department of Biostatistics
Vanderbilt University
f.harrell@vanderbilt.edu
Peterson B, George SL: Controlled Clinical Trials 14:511–522; 1993.
# Find the power of a race x treatment test. 25% of patients will
# be non-white and the total sample size is 14000.
# Accrual is for 1.5 years and minimum follow-up is 5y.
# Reduction in 5-year mortality is 15% for whites, 0% or -5% for
# non-whites. 5-year mortality for control subjects if assumed to
# be 0.18 for whites, 0.23 for non-whites.
n <- 14000
for(nonwhite.reduction in c(0,-5)) {
cat("\n\n\n% Reduction in 5-year mortality for non-whites:",
nonwhite.reduction, "\n\n")
pow <- ciapower(5, .75*n, .25*n, .18, .23, 15, nonwhite.reduction,
1.5, 5)
cat("\n\nPower:",format(pow),"\n")
}