timeroc_gof and
timeroc_predict method.This is a major release of the parTimeROC package which
enables running the Time-Dependent Receiver Operating Characteristics
(ROC) using parametric approaches. Two models were used which are based
on the Proportional Hazard and copula functions.
Several methods prepared in this package are as follows: 1.
timeroc_obj() - To create a TimeROC object. 2.
rtimeroc() - To simulate random data based on the chosen
model. 3. timeroc_fit() - To estimate model’s parameter
using either the frequentist or Bayesian. 4. timeroc_gof()
- To check the model’s goodness-of-fit. 5.
timeroc_predict() - To calculate time-dependent ROC curve
at selected time point. 6. timeroc_auc() - To calculate the
area under the time-dependent ROC curve. 7. rate_change() -
To calculate the rate change of the time-dependent ROC curve.