The functions 'age.window' and 'cal.window' in the package 'eha' are
designed to perform 'rectangular cuts' in the Lexis diagram. So, in your
case,

require(eha)
dat <- data.frame(enter = rep(0, length(Survival_days), exit =
Survival_days, event = Outcome)
dat.1 <- age.window(dat, c(0, 2190))

and 'dat.1' is your right-censored data set.

Göran Broström

On 11/21/2013 07:36 AM, Thomas Stewart wrote:
One solution is to format the data as if the follow-up period ended on day
2190.  For example,

TTT <- Survival_days
DDD <- Outcome

DDD[ TTT>2190 ] <- 0
TTT[ TTT>2190 ] <- 2190

survfit(Surv(TTT, DDD) ~ Gender)

-tgs



On Wed, Nov 20, 2013 at 3:01 PM, Dr.Vinay Pitchika
<dr.vinay....@gmail.com>wrote:

Hello R users

I have a question with Kaplan-Meier Curve with respect to my research. We
have done a retrospective study on fillings in the tooth and their survival
in relation to the many influencing factors. We had a long follow-up time
(upto 8yrs for some variables). However, we decided to stop the analysis at
the 6year follow up time, so that we can have uniform follow-up time for
all the variables.

I did play a bit with the formula and tried to stop the Kaplan-Meier curve
at my desired time (2190days)or roughly 6 years. However, my question is I
want to find the significance (log rank test) at this time point between
the two curves; because I am not able to find a way to stop the survfit at
this time point with my knowledge. Below is the code I used.

Gender2<-survfit(Surv(Survival_days, Outcome)~Gender)

plot (Gender2, xmax=2190, mark.time=FALSE, col=c(1:2), xlab="Survival time
(Days)", ylab="Survival probability", main="Gender") # mark.time=FALSE will
remove the censoring lines in the graph. If censoring lines are needed,
then remove the mark.time section in the formula.

legend("topright",c("Females", "Males"), col=(1:2), lwd=0.5)

Am sure, the code in the first line has to be modified. Please help me with
this and I will be very thankful to you.

Thanks in advance

Regards
Vinay

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