TwoSPC-package: A Package for the Analysis of Time to Event OutcomesSubject...
In SandraCastroPearson/2SPcurves: A Package for the Analysis of Time to Event Outcomes Using Two-Sample Probability Curves
TwoSPC-package R Documentation
A Package for the Analysis of Time to Event OutcomesSubject to Right-Censoring Using ROC Curves in Two-Arm Randomized Trials.
Description
Survival data is often used in clinical trials to determine effectiveness of a new treatment.
Analysis of such data is usually completed using two separate Kaplan-Meier curves, a Log Rank Test and Cox Proportional Hazard models.
We propose an alternative way to analyze this type of data by combining the two Kaplan-Meier curves into an ROC curve and using the area under the curve (AUC) as measure of treatment effectiveness.
Author(s)
Sandra Castro-Pearson, Xianghua Luo, Chap Le
See Also
Useful links:
SandraCastroPearson/2SPcurves documentation built on June 15, 2022, 3:42 a.m.
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| TwoSPC-package | R Documentation |
A Package for the Analysis of Time to Event OutcomesSubject to Right-Censoring Using ROC Curves in Two-Arm Randomized Trials.
Description
Survival data is often used in clinical trials to determine effectiveness of a new treatment. Analysis of such data is usually completed using two separate Kaplan-Meier curves, a Log Rank Test and Cox Proportional Hazard models. We propose an alternative way to analyze this type of data by combining the two Kaplan-Meier curves into an ROC curve and using the area under the curve (AUC) as measure of treatment effectiveness.
Author(s)
Sandra Castro-Pearson, Xianghua Luo, Chap Le
See Also
Useful links:
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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