ROC<-function(x,event,m=100,listdata=F,plot=T)
{
##  Author: Gillian Heller
##  17 January 2008
##
##  Computes and plots ROC curve
##  x = fitted values from logistic regression
##  event = binary response
##  m=no of points on curve
##
start <- min(x)
end <- max(x)

sens<-onemspec<-1

for (xi in seq(start+0.000001,end-0.000001,by=(end-start)/m))
	{
	tab<-table(event,x>xi)
	if( dim(tab)[2]==1) tab<-cbind(c(0,0),tab)
	sens<-c(sens,tab[2,2]/(tab[2,2]+tab[2,1]))
	onemspec<-c(onemspec,tab[1,2]/(tab[1,2]+tab[1,1]))
	}

sens<-c(sens,0)
onemspec<-c(onemspec,0)
if(plot)
	{plot(onemspec,sens,type="n",xlab="1-specificity",ylab="Sensitivity")
	lines(lowess(onemspec,sens,f=0.2))
	#text(onemspec,sens,seq(start+0.000001,end-0.000001,by=(end-start)/m))
}
if(listdata)list(sens=sens,onemspec=onemspec)
}