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.

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

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.

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 (Optional[float]) – 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.