Melano

<p>This example dataset is included for illustration. The Melano data is publicly available.
   In 1962-1977, 205 patients with malignant melanoma (skin cancer) had a radical
   operation performed at an academic medical center. At the end of the follow-up,
   57 died from cancer, 14 died from other causes, and the other 134 patients were
   alive (censored). This example dataset illustrates the prediction accuracy of
   competing risk outcomes with baseline age and tumor thickness.</p>

datasets

The tdROC package facilitates the estimation of time-dependent ROC
(Receiver Operating Characteristic) curves and the Area Under the time-dependent
ROC Curve (AUC) in the context of survival data, accommodating scenarios with
right censored data and the option to account for competing risks. In addition
to the ROC/AUC estimation, the package also estimates time-dependent Brier score and
survival difference. Confidence intervals of various estimated quantities can be
obtained from bootstrap. The package also offers plotting functions for visualizing
time-dependent ROC curves.

Xiaoyang Li

tdROC

Nonparametric Estimation of Time-Dependent ROC, Brier Score, and
Survival Difference from Right Censored Time-to-Event Data with
or without Competing Risks

Zhe Yin

Liang Li

Melano function

<p>A data frame with 312 observations and 4 variables: time (event time/censoring), time), censor (censoring
        mayoscore4, mayoscore5. The two scores are derived from 4 and 5 covariates
       respectively.</p>

Melano: Example data: Malignant Melanoma Data

Description

Usage

Arguments

Format

References

Examples