log-rank (or other) test for difference between survival curves

#1
Hi, all.

I have co-opted some R code that estimates parameters for a Gompertz-Makeham mortality model. The data to which the model is fit is interval censored, with counts of individuals in each age-range category. For example:

Code:
naga <- structure(c(15,20,35,50,20,35,50,Inf,46,310,188,101),.Dim=as.integer(c(4,3)),.Dimnames=list(NULL,c("col1","col2","col3")))
The first and second columns are lower/upper limits for each age-range category; the third column is the number of individuals observed in each group. The Gompertz-Makeham parameters are estimated by the following function:

Code:
GM.naga <- function(x,deaths=naga)
	{
		a2=x[1]
		a3=x[2]
		b3=x[3]
		shift<-15
		nrow<-NROW(deaths)
		
		S.t<-function(t)
			{
				return(exp(-a2*(t-shift)+a3/b3*(1-exp(b3*(t-shift)))))
			}
		
		d<-S.t(deaths[1:nrow,1])-S.t(deaths[1:nrow,2])
    obs<-deaths[,3]
    lnlk<-as.numeric(crossprod(obs,log(d)))
    return(lnlk)
}
optim(c(0.001, 0.01, 0.1),GM.naga,control=list(fnscale=-1))
And to get the survival values at each age, from 15-70 years...

Code:
surv_GM.naga <- function (t)
	{
		x=c(5.227131e-09, 2.208408e-02, 4.577932e-02)
		a2<-x[1]		
		a3<-x[2]
		b3<-x[3]
		shift<-15
		
		S.t<-exp(-a2*(t-shift)+a3/b3*(1-exp(b3*(t-shift))))
		return<-S.t
		print(S.t)
}

surv_GM.naga(15:70)
If I estimated hazard parameters for another sample, how could I compare the two survival distributions to see if they are significantly different? Thanks.

--Trey