Menu location: Analysis_Sample Size_Survival Times.
This function gives you the minimum number of subjects that you require to detect a true ratio of median survival times (hr) with power POWER and two sided type I error probability ALPHA (Dupont, 1990; Schoenfeld and Richter, 1982).
The method used here is suitable for calculating sample sizes for studies that will be analysed by the log-rank test.
Information required
POWER: probability of detecting a real effect
ALPHA : probability of detecting a false effect (two sided: double this if you need one sided)
A : accrual time during which subjects are recruited to the study
F : additional follow-up time after the end of recruitment
* input either (C and r) or (C and E), where r=E/C
C: median survival time for control group
E: median survival time for experimental group
r : hazard ratio or ratio of median survival times
M: number of controls per experimental subject
Practical issues
Usual values for POWER are 80%, 85% and 90%; try several in order to explore/scope.
5% is the usual choice for ALPHA.
C is usually estimated from previous studies.
If possible, choose a range of hazard ratios that you want have the statistical power to detect.
Technical validation
The estimated sample size per group n is calculated as:
- where a = alpha, b = 1 - power and Zp is the standard normal deviate for probability p. n is rounded up to the closest integer. (1+1/m)/p is equivalent to 2/p in the first equation if the experimental and control group sizes are unequal.