crrstep: Stepwise Covariate Selection for the Fine & Gray Competing Risks Regression Model

Performs forward and backwards stepwise regression for the Proportional subdistribution hazards model in competing risks (Fine & Gray 1999). Procedure uses AIC, BIC and BICcr as selection criteria. BICcr has a penalty of k = log(n*), where n* is the number of primary events.

Author
Ravi Varadhan & Deborah Kuk
Date of publication
2015-02-23 23:17:17
Maintainer
Ravi Varadhan <ravi.varadhan@jhu.edu>
License
GPL (>= 2)
Version
2015-2.1

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Man pages

crrstep
Stepwise regression for competing risks regression
crrstep-package
Stepwise regression procedure for the Fine & Gray regression...

Files in this package

crrstep
crrstep/inst
crrstep/inst/NEWS.Rd
crrstep/NAMESPACE
crrstep/R
crrstep/R/crrstep.r
crrstep/MD5
crrstep/DESCRIPTION
crrstep/man
crrstep/man/crrstep.Rd
crrstep/man/crrstep-package.Rd