subsample_survival_evaluation: Likelihood ratio analysis of Cox PH survival models for...

In vittoriofortino84/COPS: Clustering algorithms for Omics-driven Patient Stratification

Likelihood ratio analysis of Cox PH survival models for clustering results

Description

Likelihood ratio analysis of Cox PH survival models for clustering results

Usage

subsample_survival_evaluation(
  event_data,
  clusters,
  survival_time_col = "time",
  survival_event_col = "event",
  survival_covariate_names = NULL,
  row_id = "ID",
  by = c("run", "fold", "datname", "drname", "k", "m"),
  parallel = 1,
  ...
)

Arguments

event_data	A data.frame that contains survival times, event data and covariates.
clusters	A data.frame or data.table containing clustering information.
survival_time_col	Name of the column in event_data that contains survival time.
survival_event_col	Name of the column in event_data that contains event indicators.
survival_covariate_names	Names of covariate columns in event_data.
row_id	Name of column in event_data that matches sample IDs in clusters.
by	Vector of column names that identify a single clustering result in clusters.
parallel	number of parallel threads
...	Extra arguments are ignored.

Value

data.table of Cox PH LRT-test p-values and Harrell's concordance index values

vittoriofortino84/COPS documentation built on Jan. 28, 2025, 3:16 p.m.