# EVaddGam: Relative risk for additive gamma model In mets: Analysis of Multivariate Event Times

## 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

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)
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)
## MZ
# dim(dout\$theta.des)
# dout\$random.design[,,1]
## DZ
# dout\$theta.des[,,nrow(pairs)]
# dout\$random.design[,,nrow(pairs)]
#