Implementation of the following methods for event history analysis. Risk regression models for survival endpoints also in the presence of competing risks are fitted using binomial regression based on a time sequence of binary event status variables. A formula interface for the FineGray regression model and an interface for the combination of causespecific Cox regression models. A toolbox for assessing and comparing performance of risk predictions (risk markers and risk prediction models). Prediction performance is measured by the Brier score and the area under the ROC curve for binary possibly timedependent outcome. Inverse probability of censoring weighting and pseudo values are used to deal with right censored data. Lists of risk markers and lists of risk models are assessed simultaneously. Crossvalidation repeatedly splits the data, trains the risk prediction models on one part of each split and then summarizes and compares the performance across splits.
Package details 


Author  Thomas Alexander Gerds, Thomas Harder Scheike, Paul Blanche, Brice Ozenne 
Date of publication  20170630 17:35:24 UTC 
Maintainer  Thomas Alexander Gerds <tag@biostat.ku.dk> 
License  GPL (>= 2) 
Version  1.4.3 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.