Survival Analysis
Kaplan–Meier median survival with a nonparametric Brookmeyer–Crowley confidence interval for right-censored data. Enter one follow-up time and event indicator per subject; the calculation runs entirely in your browser.
The calculator first estimates the survival function with the Kaplan–Meier product-limit estimator. The median is the first time at which the estimated survival curve is at or below 0.50.
The confidence interval for the median is obtained by inverting a confidence band for the Kaplan–Meier survival function. This is the nonparametric approach introduced by Brookmeyer and Crowley (1982) for arbitrarily right-censored survival data.
Brookmeyer, R. & Crowley, J. (1982). A confidence interval for the median survival time. Biometrics, 38(1), 29–41. doi:10.2307/2530286.
Kaplan, E. L. & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481.
this method lists median-survival confidence procedures within its survival-analysis software family; the underlying nonparametric median interval used here is the Brookmeyer–Crowley method. The R survival documentation provides an independent implementation reference for Kaplan–Meier confidence limits and the log–log transformation.
Validation example: Gehan’s 6-MP group has 21 patients, 9 events, and 12 censored observations. Using the 21 time/event pairs preloaded above and a 95% log–log interval gives a median of 23 weeks, a lower 95% limit of 13 weeks, and no finite upper limit.