Average Positive Predictive Values (AP) for Binary Outcomes and Censored Event Times
Released Aug 5, 2016 by Hengrui Cai, Yan Yuan, Qian Michelle Zhou, Bingying Li
We provide tools to estimate two prediction performance metrics, the average positive predictive values (AP) as well as the well-known AUC (the area under the receiver operator characteristic curve) for risk scores or marker. The outcome of interest is either binary or censored event time. Note that for censored event time, our functions estimate the AP and the AUC are time-dependent for pre-specified time interval(s). A function that compares the APs of two risk scores/markers is also included. Optional outputs include positive predictive values and true positive fractions at the specified marker cut-off values, and a plot of the time-dependent AP versus time (available for event time data).
This package can be included as a dependency from a Java or Scala project by including
the following your project's
about embedding Renjin in JVM-based projects.
<dependencies> <dependency> <groupId>org.renjin.cran</groupId> <artifactId>APtools</artifactId> <version>3.0-b13</version> </dependency> </dependencies> <repositories> <repository> <id>bedatadriven</id> <name>bedatadriven public repo</name> <url>https://nexus.bedatadriven.com/content/groups/public/</url> </repository> </repositories>
If you're using Renjin from the command line, you load this library by invoking:
This package was last tested against Renjin 0.8.2523 on Nov 12, 2017.