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WPC (version 1.0)
Weighted Predictiveness Curve
Description
Implementing weighted predictiveness curve to visualize the marker-by-treatment relationship and measure the performance of biomarkers for guiding treatment decision.
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Version
Version
1.0
Install
install.packages('WPC')
Monthly Downloads
16
Version
1.0
License
LGPL (>= 2)
Maintainer
Hui Yang
Last Published
July 30th, 2016
Functions in WPC (1.0)
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surv.rate
Calculate Survival Rate at a Fix Time Point
TrioWPCCurve
Generate Three Weighted Predictiveness Curves in Graph
TrioScattorPlot
Generate Scatter Plots for Time-to-Event and Biomarkers for Three Groups
SoloWPCCurve
Generate Single Weighted Predictiveness Curve in Graph
DuoWPCCurve
Generate Two Weighted Predictiveness Curves in Graph
SoloScattorPlot
Generate Scatter Plots for Time-to-Event and Biomarkers for One Group
DuoScattorPlot
Generate Scatter Plots for Time-to-Event and Biomarkers for Two Groups
WPC-package
Implement Weighted Predictiveness Curve to Visualize the Marker-by-Treatment Relationship and Measure the Performance of Biomarkers for Guiding Treatment Decision.
wpcdata
A Data Example to Illustrate WPC Approach.
ns.windows
Create a Series of Overlapping Windows by Fixing Number of Patients within each Window
cox.wpc.est
Generate Weighted Predictiveness Curve Estimates Using Parametric Approach.
ww.windows
Create a Series of Overlapping Windows by Fixing Biomarker Scale Window Width
npr.wpc.est
Generate Weighted Predictiveness Curve Estimates Using Non-Parametric Approach.