fast_roc_calculation: Fast calculation of AUC for ROC using parallel strategy

Description Usage Arguments Value Author(s) Examples

View source: R/fast_roc_calculation.R

Description

This function is used to create time-dependent ROC curve from censored survival data using the Kaplan-Meier (KM) or Nearest Neighbor Estimation (NNE) method of Heagerty, Lumley and Pepe, 2000

Usage

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fast_roc_calculation(test_matrix, y_surv, predict_time = 5, roc_method = "NNE")

Arguments

test_matrix

Test matrix used in the analysis. Colmuns are samples, rows are markers.

y_surv

Survival information created by Surv function in survival package.

predict_time

Time point of the ROC curve, default is 5 year.

roc_method

Method for fitting joint distribution of (marker,t), either of KM or NNE, the default method is NNE.

Value

This will retrun a numeric vector contains AUC results for each row in test_matrix.

Author(s)

Xin Yu

Examples

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data(demo_survival_data)
data('demo_data',package = "EnMCB")
demo_set<-demo_data$realdata
res<-fast_roc_calculation(demo_set[1:2,],demo_survival_data)

EnMCB documentation built on Dec. 22, 2020, 2 a.m.