Sample size calculation: Survival analysis (logrank test)
Survival analysis (logrank test)
Calculates the required sample size for the comparison of survival rates in two independent groups.
- Type I error - alpha: the probability of making a Type I error (α-level, two-sided), i.e. the probability of rejecting the null hypothesis when in fact it is true.
- Type II error - beta: the probability of making a Type II error (β-level), i.e. the probability of accepting the null hypothesis when in fact it is false.
- Survival rate Group 1: the hypothesized survival rate in the first group.
- Survival rate Group 2: the hypothesized survival rate in the second group.
- Ratio of sample sizes in Group 1 / Group 2: the ratio of the sample sizes in group 1 and 2. Enter 1 for equal sample sizes in both groups. Enter 2 if the number of cases in group 1 must be double of the number of cases in group 2.
You are interested in detecting a difference between survival rates of 0.6 and 0.4. You plan to have twice as many cases in the first group as in the second group.
For α-level you select 0.05 and for β-level you select 0.20 (power is 80%).
Enter the values 0.6 and 0.4 for the Survival rates in Group 1 and Group 2, and enter 2 for the Ratio of sample sizes.
After you click Calculate the program displays the required sample size.
In the example 129 cases are required in Group 1 and 65 cases in Group 2, giving a total of 194 cases.
A table shows the required total sample size for different Type I and Type II Error levels.
- Machin D, Campbell MJ, Tan SB, Tan SH (2009) Sample size tables for clinical studies. 3rd ed. Chichester: Wiley-Blackwell.
Sample Size Tables for Clinical Studies
David Machin, Michael J. Campbell, Say-Beng Tan, Sze-Huey Tan
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