Survival analysis on small sample : Chi-square test or Fisher's exact test? I'm running a survival analysis on a sample of 26 patients, divided into 2 groups according to certain variables and different times ( because there is censored data). I couldn't perform the log-rank test because of the small sample size, so I'm thinking of performing a Fisher's exact test.
What should be the best test to handle the small sample size?

The log-rank test does not require large samples: we can get an exact test by simply doing a permutations test on the log-rank statistic itself.
For an implementation in R, here is one example. This particular example is for interval censored data, which is a more general form of censoring than right censored, so can be applied to data that is only right censored. For simplicity there may be an implementation for right-censored only data somewhere.
