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Type: Package
Title: R2 Measure of Explained Variation under the Additive Hazards Model
Version: 0.1.0
Date: 2020-03-20
Author: Denise Rava
Maintainer: Denise Rava <drava@ucsd.edu>
Description: R^2 measure of explained variation under the semiparametric additive hazards model is estimated. The measure can be used as a measure of predictive capability and therefore it can be adopted in model selection process. Rava, D. and Xu, R. (2020) <doi:10.48550/arXiv.2003.09460>.
License: GPL-2
Encoding: UTF-8
LazyData: true
RdMacros: Rdpack
Imports: ahaz, pracma, zoo, caTools, survival, Rdpack (≥ 0.7)
NeedsCompilation: no
Packaged: 2020-04-06 19:38:37 UTC; Denise
Repository: CRAN
Date/Publication: 2020-04-07 15:20:02 UTC

Estimate R^2 for additive hazards model

Description

The function computes R^2 measure of explained variation under the semiparametric additive hazards model.

Usage

R2addhaz(data)

Arguments

data

a data.frame with survival data. The first column needs to be the censored failure time. The second column needs to be the event indicator, 1 if the event is observed, 0 if it is censored. The other columns are covariates.

Details

The semiparametric hazards model

\lambda(t | Z)=\lambda_0(t) + \beta Z

is fitted to the data. The R^2 measure of explained variation is then computed.

Value

R

R^2 measure of explained variation.

Author(s)

Denise Rava

References

Rava, D., Xu, R. "Explained Variation under the Additive Hazards Model", March 2020, arXiv:2003.09460

Examples

Z=runif(100,0,sqrt(3)) #generate covariates
u=runif(100,0,1)
t=-log(u)/as.vector((1+Z)) #generate failure time
status=rep(1,100) #censoring indicator
sd<-as.data.frame(cbind(t,status,Z)) #data frame of survival data
R2addhaz(sd)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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