Survival Analysis · LOGRANK-2I

Sample Size for Comparing Two Independent Survival Curves

Plan an event-driven two-group survival study using the log-rank test under proportional hazards.

1. Planning setup

Planning mode

Median survival times are converted to constant hazards using an exponential survival model. Use the selected time unit consistently.

Time unit

Use the selected unit consistently for time-based inputs.

2. Information obtained from previous study / literature

Median survival in control / unexposed group

3. Information decided by the researcher

Median survival in experimental / exposed group

Accrual duration

Use the selected time unit.

Additional follow-up after accrual closes

Alternative

Significance level, alpha

Power (%)

Allocation ratio, N1/N2

Anticipated dropout/non-response (%)

4. Results

Enter the study assumptions and select Calculate.

Formula, assumptions, limitations, and methodological note

Example clinical scenario

A randomized oncology trial compares progression-free survival between a new treatment and standard therapy using a two-group log-rank test.

Formula and methodological note

Uses Schoenfeld's log-rank event requirement under proportional hazards. Median-survival and landmark-survival modes derive constant hazards, assume exponential survival, and use uniform accrual.

An event is the prespecified endpoint, not censoring or loss to follow-up. This tool supports planning and does not replace statistical consultation.

Median-survival mode may be inappropriate when hazards vary substantially over time or proportional hazards are implausible. Not for paired groups, more than two groups, non-proportional hazards, RMST, competing risks, recurrent events, cluster designs, non-inferiority/equivalence, or group-sequential monitoring.

Method references

Schoenfeld D. The asymptotic properties of nonparametric tests for comparing survival distributions. Biometrika. 1981;68:316–319.
Schoenfeld DA. Sample-size formula for the proportional-hazards regression model. Biometrics. 1983;39:499–503.
Schoenfeld DA, Richter JR. Nomograms for calculating the number of patients needed for a clinical trial with survival as an endpoint. Biometrics. 1982;38:163–170.
Lachin JM, Foulkes MA. Evaluation of sample size and power for analyses of survival with allowance for nonuniform patient entry, losses to follow-up, noncompliance, and stratification. Biometrics. 1986;42:507–519.
Cox DR. Regression models and life-tables. J R Stat Soc Series B Stat Methodol. 1972;34:187–220.
Wu J. Statistical Methods for Survival Trial Design. Boca Raton (FL): CRC Press; 2018.

Suggested citation

Yaacob, Najib Majdi. “Sample Size for Comparing Two Independent Survival Curves (LOGRANK-2I).” Web calculator. NajibMY, 2026. Accessed July 29, 2026. https://najibmy.netlify.app/tools/sample-size/survival-analysis/comparing-two-independent-survival-curves/.