EVaddGam: Relative risk for additive gamma model

View source: R/twostage.R

EVaddGamR Documentation

Relative risk for additive gamma model

Description

Computes the relative risk for additive gamma model at time 0

Usage

EVaddGam(theta, x1, x2, thetades, ags)

Arguments

theta

theta

x1

x1

x2

x2

thetades

thetades

ags

ags

Author(s)

Thomas Scheike

References

Eriksson and Scheike (2015), Additive Gamma frailty models for competing risks data, Biometrics (2015)

Examples

lam0 <- c(0.5,0.3)
pars <- c(1,1,1,1,0,1)
## genetic random effects, cause1, cause2 and overall
parg <- pars[c(1,3,5)]
## environmental random effects, cause1, cause2 and overall
parc <- pars[c(2,4,6)]

## simulate competing risks with two causes with hazards 0.5 and 0.3
## ace for each cause, and overall ace
out <- simCompete.twin.ace(10000,parg,parc,0,2,lam0=lam0,overall=1,all.sum=1)

## setting up design for running the model
mm <- familycluster.index(out$cluster)
head(mm$familypairindex,n=10)
pairs <- matrix(mm$familypairindex,ncol=2,byrow=TRUE)
tail(pairs,n=12)
#
kinship <- (out[pairs[,1],"zyg"]=="MZ")+ (out[pairs[,1],"zyg"]=="DZ")*0.5

# dout <- make.pairwise.design.competing(pairs,kinship,
#          type="ace",compete=length(lam0),overall=1)
# head(dout$ant.rvs)
## MZ
# dim(dout$theta.des)
# dout$random.design[,,1]
## DZ
# dout$theta.des[,,nrow(pairs)]
# dout$random.design[,,nrow(pairs)]
#
# thetades <- dout$theta.des[,,1]
# x <- dout$random.design[,,1]
# x
##EVaddGam(rep(1,6),x[1,],x[3,],thetades,matrix(1,18,6))

# thetades <- dout$theta.des[,,nrow(out)/2]
# x <- dout$random.design[,,nrow(out)/2]
##EVaddGam(rep(1,6),x[1,],x[4,],thetades,matrix(1,18,6))

mets documentation built on Oct. 2, 2022, 5:06 p.m.