Nothing
"ahaz.adjust"<-function(surv,X,weights,idx,method=c("coef","z","crit"))
{
## Purpose: Fast calculation of univariate measures of association for columns in X,
## adjusted for covariates specified in 'idx'
## ----------------------------------------------------------------------
## Arguments:
## surv : Surv object (right censored/counting process)
## X : Numeric matrix of covariates
## weights : Weight vector (nonnegative)
## idx : Which columns to adjust for?
## method : Adjustment method
## ----------------------------------------------------------------------
## Author: Anders Gorst-Rasmussen
this.call <- match.call()
method<-match.arg(method)
if(missing(idx) || !is.numeric(idx) || any(idx<1) || any(idx>ncol(X)))
stop("'idx' incorrectly specified")
idx<-as.integer(idx)
idx <- sort(idx)
if(method == "z")
{
# Partial solutions for covariates in 'idx
m<-ahaz.partial(surv, X, weights, idx = idx)
Dbig<-m$D
Bbig<-m$B
# Covariates in 'idx' only
Borig<-Bbig[,idx]
Dorig<-Dbig[,idx]
# Univariate results
muni<-ahaz(surv,X, weights, univariate=TRUE)
d<-muni$d
D<-muni$D
iA<-solve(Dorig)
n<-ncol(iA)
vf<-iA%*%Dbig
ik<-1/(D-apply(Dbig*vf,2,sum))
x1<--ik*t(vf)
nomin<-x1%*%d[idx]+ik*d
denomin<-ik^2*muni$B+2*ik*apply(Bbig*t(x1),2,sum)+apply(t(x1) * (Borig%*%t(x1)), 2, sum)
denomin[idx]<-NA
nomin[idx]<-NA
adj<-nomin/sqrt(denomin)
# return(adj)
} else {
m1<-ahaz.partial(surv=surv,X=X,weights=weights, idx=idx)
m3<-ahaz(surv=surv,X=X,weights=weights, univariate=TRUE)
DD<-m1$D
iA<-solve(DD[,idx])
D<-m3$D
d<-m3$d
n<-ncol(iA)
vf<-iA%*%DD
ik<-1/(D-apply(DD*vf,2,sum))
x1<--ik*t(vf)%*%d[idx]
x2<-ik*d
adj<-x1+x2
adj[idx]<-NA
if(method!="coef"){
adj<--(ik*d^2+2*d*x1+x1^2/ik)
adj[idx]<-NA
}
}
return(list("call"=this.call,"idx"=idx,"adj"=drop(adj)))
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.