# [R] Time Dependent Cox Model

quaildoc just.struttin at gmail.com
Wed Oct 14 21:19:20 CEST 2009

```Some suggested that go into more detail on what I wanted to accomplish and
the rest of my code.  I want to accomplish exactly what Fox did in this
article( http://www.nabble.com/file/p25897307/appendix-cox-regression.pdf
appendix-cox-regression.pdf ) (starting with page 7), except using "habitat"
instead of employment. I want habitat to be a time dep. covariate and it
varys by day.

I read in my data as the csv. file, and one major difference in the data set
Fox used and min is I have a DaysatRisk column instead of the "week" the
person went back to jail. This I think is the root of my problem calculating
the proper death.time.  The death.time column should be 1s and 0s that
corresponds to the day the animal died.

sum(!is.na(surv[,16:726]))

surv2<-matrix(0,12329,19)
colnames(surv2)<-c('start', 'stop', 'death.time',
names(surv)[1:15],'habitat')
row<-0 # set record counter to 0
for (i in 1:nrow(surv)) { # loop over individuals
for (j in 16:726) { # loop over 52 weeks
if (is.na(surv[i, j])) next # skip missing data
else {
row <- row + 1 # increment row counter
start <- j - 11 # start time (previous week)
stop <- start + 1 # stop time (current week)
death.time <- if (stop == surv[i, 4] && surv[i, 5] ==1) 1 else 0
# construct record:
surv2[row,] <- c(start, stop, death.time, unlist(surv[i, c(1:15,
j)]))
}
}
}
surv2<-as.data.frame(surv2)
remove(i,j,row,start,stop,death.time)

surv2[1:15,]

test<-coxph(Surv(start,stop,death.time)~habitat, data=surv2)

JorisMeys wrote:
>
> Well,
>
> it might be wise to elaborate a bit more about the variables and what
> exactly you want e.g. death-time to be. I'd interprete it as time of
> death, but the fact that it is 0/1, means it is a logical (?) binary
> variable of some sort.
>
> the dataset and your research, can still understand what is inside the
> dataset and what exactly you're trying to obtain.
>
> I'd also suggest to add the command to read in the data. I don't have
> the time to spend looking around how exactly I can read in the dataset
> in such a way it fits what you have in your workspace.
>
> Cheers
> Joris
>
> On Wed, Oct 14, 2009 at 5:37 PM, quaildoc <just.struttin at gmail.com> wrote:
>>
>> Does anyone have suggestions? Thanks!
>>
>> quaildoc wrote:
>>>
>>> I am having trouble formatting some survival data to use in a time
>>> dependent cox model. My time dep. variable is habitat and I have it
>>> recorded for every day (with some NAs).  I think it is working properly
>>> except for calculating the death.time. This column should be 1s or 0s
>>> and
>>> as I have it only produces 0s.  Any help will be greatly appreciated.
>>>
>>>
>>>  http://www.nabble.com/file/p25881478/Survival_master2.csv
>>> Survival_master2.csv
>>>
>>>
>>>
>>>  Here is my code:
>>> sum(!is.na(surv[,16:726]))
>>>
>>> surv2<-matrix(0,12329,19)
>>> colnames(surv2)<-c('start', 'stop', 'death.time',
>>> names(surv)[1:15],'habitat')
>>> row<-0 # set record counter to 0
>>>     for (i in 1:nrow(surv)) { # loop over individuals
>>>         for (j in 16:726) { # loop over 726 days
>>>           if (is.na(surv[i, j])) next # skip missing data
>>>           else {
>>>             row <- row + 1 # increment row counter
>>>             start <- j - 11 # start time (previous day)
>>>             stop <- start + 1 # stop time (day)
>>>             death.time <- if (stop == surv[i, 4] && surv[i, 5] ==1) 1
>>> else
>>> 0
>>>                    # construct record:
>>>             surv2[row,] <- c(start, stop, death.time, unlist(surv[i,
>>> c(1:15, j)]))
>>>             }
>>>         }
>>>    }
>>> surv2<-as.data.frame(surv2)
>>>
>>
>> --
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>>
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>
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