ciapower function

Power of Interaction Test for Exponential Survival

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)

Arguments

• 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

Returns

power

Side Effects

prints

AUTHOR

Frank Harrell

Department of Biostatistics

Vanderbilt University

fh@fharrell.com

References

Peterson B, George SL: Controlled Clinical Trials 14:511--522; 1993.

See Also

cpower, spower

Examples

# 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")
}