# Sample size calculation: Survival analysis (logrank test)

Command: | Sample size Survival analysis (logrank test) |

## Description

Calculates the required sample size for the comparison of survival rates in two independent groups.

## Required input

- 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.

## Example

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.

## Results

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.

## Literature

- Machin D, Campbell MJ, Tan SB, Tan SH (2009) Sample size tables for clinical studies. 3
^{rd}ed. Chichester: Wiley-Blackwell.

## See also

## Recommended book

## Sample Size Tables for Clinical Studies

David Machin, Michael J. Campbell, Say-Beng Tan, Sze-Huey Tan

Buy from Amazon US - CA - UK - DE - FR - ES - IT

Sample Sizes for Clinical, Laboratory and Epidemiology Studies includes the sample size software (SSS) and formulae and numerical tables needed to design valid clinical studies. The text covers clinical as well as laboratory and epidemiology studies and contains the information needed to ensure a study will form a valid contribution to medical research.

The authors, noted experts in the field, explain step by step and explore the wide range of considerations necessary to assist investigational teams when deriving an appropriate sample size for their when planned study. The book contains sets of sample size tables with companion explanations and clear worked out examples based on real data. In addition, the text offers bibliography and references sections that are designed to be helpful with guidance on the principles discussed.