Note

This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.

biolearn.mortality.calculate_log_rank_test

biolearn.mortality.calculate_log_rank_test(data, predictor_results)

Calculates the log-rank test for each predictor in the predictor_results DataFrame, adjusted for age.

Parameters:

• data (Dataset) – A Dataset object containing metadata with columns: ‘dead’ - boolean indicating if the subject is dead ‘years_until_death’ - if dead this should be years between sample collection and death. Otherwise years between sample collection and last known contact with live subject ‘age’ - age of the subject at sample collection

• predictor_results (pd.DataFrame) – The DataFrame containing predictor results. Columns are the name of the predictor model and rows must be ids from data

Returns:

A DataFrame containing log-rank test statistics and p-values for each predictor.

Return type:

pd.DataFrame