Model-Based Estimation of Confounder-Adjusted Attributable Fractions
Released Feb 11, 2017 by Elisabeth Dahlqwist
Estimates the attributable fraction in different sampling designs adjusted for measured confounders using logistic regression (cross-sectional and case-control designs), conditional logistic regression (matched case-control design), Cox proportional hazard regression (cohort design with time-to- event outcome) and gamma-frailty model with a Weibull baseline hazard. The variance of the estimator is obtained by combining the delta method with the the sandwich formula. Dahlqwist et al.(2016)
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>AF</artifactId> <version>0.1.4-b12</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 0.8.2543 on Dec 17, 2017.