Saved Search

Survival Analysis · SURV-CI

Sample Size for Estimating One Survival Probability

Plan a landmark Kaplan–Meier survival estimate with a chosen pointwise confidence-interval margin of error.

Enter survival, confidence level, and margin of error as percentages.

1. Planning setup

Use the selected unit consistently for all time inputs.

2. Information obtained from previous study / literature

3. Information decided by the researcher

Assumes exponential survival, uniform accrual, independent administrative censoring, and a pointwise asymptotic Kaplan–Meier confidence interval.

4. Results

Enter assumptions and select Calculate.

Formula, assumptions, limitations, and methodological note

Example clinical scenario

A transplant programme wants to estimate one-year graft-survival probability with specified precision while accounting for censoring.

Formula and methodological note

Uses asymptotic pointwise Kaplan–Meier variance under exponential survival and administrative censoring. It is not an ordinary binomial-proportion calculation except in the analytic no-censoring special case.

Not for median survival, confidence bands, tests, competing risks, recurrent events, interval censoring, clusters, or arbitrary censoring distributions.

Method references

  1. Kaplan EL, Meier P. Nonparametric estimation from incomplete observations. J Am Stat Assoc. 1958;53:457–481.
  2. Breslow N, Crowley J. A large sample study of the life table and product-limit estimates under random censorship. Ann Stat. 1974;2:437–453.
  3. Thomas DR, Grunkemeier GL. Confidence interval estimation of survival probabilities for censored data. J Am Stat Assoc. 1975;70:865–871.
  4. Greenwood M. A Report on the Natural Duration of Cancer. London: HMSO; 1926.

Suggested citation

Yaacob, Najib Majdi. “Sample Size for Estimating One Survival Probability (SURV-CI).” Web calculator. NajibMY, 2026. Accessed July 29, 2026. https://najibmy.netlify.app/tools/sample-size/survival-analysis/estimating-one-survival-probability/.