ehrapy.tools.test_kmf_logrank

ehrapy.tools.test_kmf_logrank(kmf_A, kmf_B, t_0=-1, weightings=None)[source]

Calculates the p-value for the logrank test comparing the survival functions of two groups.

Measures and reports on whether two intensity processes are different. That is, given two event series, determines whether the data generating processes are statistically different. The test-statistic is chi-squared under the null hypothesis.

See https://lifelines.readthedocs.io/en/latest/lifelines.statistics.html

Parameters:

  • kmf_A (KaplanMeierFitter) – The first KaplanMeierFitter object containing the durations and events.

  • kmf_B (KaplanMeierFitter) – The second KaplanMeierFitter object containing the durations and events.

  • t_0 (float | None) – The final time period under observation, and subjects who experience the event after this time are set to be censored. Specify -1 to use all time. Defaults to -1.

  • weightings (Optional[Literal['wilcoxon', 'tarone-ware', 'peto', 'fleming-harrington']]) – Apply a weighted logrank test: options are “wilcoxon” for Wilcoxon (also known as Breslow), “tarone-ware” for Tarone-Ware, “peto” for Peto test and “fleming-harrington” for Fleming-Harrington test. These are useful for testing for early or late differences in the survival curve. For the Fleming-Harrington test, keyword arguments p and q must also be provided with non-negative values.

Return type:

StatisticalResult

Returns:

The p-value for the logrank test comparing the survival functions of the two groups.