# The Safe Logrank Test: Error Control under Continuous Monitoring with Unlimited Horizon

@inproceedings{Schure2020TheSL, title={The Safe Logrank Test: Error Control under Continuous Monitoring with Unlimited Horizon}, author={Judith ter Schure and Mar{\'i}a P{\'e}rez-Ortiz and Amanda Ly and Peter D. Grunwald}, year={2020} }

We introduce the safe logrank test, a version of the logrank test that provides type-I error guarantees under optional stopping and optional continuation. The test is sequential without the need to specify a maximum sample size or stopping rule and allows for cumulative meta-analysis with type-I error control. The method can be extended to define anytime-valid confidence intervals. All these properties are a virtue of the recently developed martingale tests based on E-variables, of which the…

## 5 Citations

### ALL-IN meta-analysis: breathing life into living systematic reviews

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The method for time-to-event data is illustrated, showing how synthesizing data at interim stages of studies can increase efficiency when studies are slow in themselves to provide the necessary number of events for completion.

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Comparison to p-value analysis in simulations and a real-world example show that E-variables, through their flexibility, often allow for early stopping of data collection, thereby retaining similar power as classical methods.

### ALL-IN meta-analysis: breathing life into living systematic reviews

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### Safe Testing

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Sharing Fisherian, Neymanian and Jeffreys-Bayesian interpretations, S-values and safe tests may provide a methodology acceptable to adherents of all three schools.

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