st: R: data prep for survival analysis with time varying covariate

[<carlo.lazzaro@tiscalinet.it>]

Dear Kyleigh,
I have expanded a  bit the chuck of dataset you provided the list with (10
patients, one failure each during the analysis time; patients are gathered
in two different groups (drugs, with a 0/1 dummy)), as in its original
version was impossible to analyze (too few observations). Two Cox
regressions were performed, considering either variable Waittime constant
over time (-stcox drugs Waittime-), or  variable Waittime varying with time
(interacting with a square root function of analysis time: -stcox drugs,
tvc(Waittime) texp((_t)^.5)-).
It's up to you to verify whether  these assumptions (cox regression and tvc,
namely) fit your research issue.                                   
HTH and Kind Regards,
Carlo
...............................code
starts.......................................
input ID      Timetoevent     Event   Waittime
1       50                      0       40
2       73                      0       8
3       150                     1       100
4       100                     0       50
5        70                     0       10
6        35                     0       60
7       120                     1       80
8        20                     1        0
9       140                     0       100
10       200                    1        30
end
stset Timetoevent, id(ID) failure(Event==1)
g drugs=1 in 1/5
replace drugs=0 if drugs==.
stcox drugs Waittime                                           
stcox drugs, tvc(Waittime) texp((_t)^.5)         
............................code
ends.................................................

-----Messaggio originale-----
Da: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Kyleigh Schraeder
Inviato: giovedì 19 gennaio 2012 00:20
A: statalist@hsphsun2.harvard.edu
Oggetto: st: data prep for survival analysis with time varying covariate

Hi Dr. Gagnon,

This is the first time I'm using a survival analysis so I hope my questions
make sense.

My variables are: id, timetoevent (in days), event, and waittime.

In my study, every patient has their own start time or time 0.  At time 0,
each patient is put on a wait-list.  Some patients may still be waiting when
the 'event' happens (they should be censored).
However, some patients may come off of the wait list and receive services.
Thus, some patients are technically 'not waiting' for a period of time
before the event occurs.  So, as I understand, 'waittime' is a time-varying
covariate.

I am interested in examining the effect of a patient's wait-time on the
outcome (whether the event occurs). In other words, what is the probability
of the event occuring for patient X, given their waiting time. Right now my
data is currently set up where each participant has their own row of data.

ID      Timetoevent     Event   Waittime
1       50                      0       40
2       73                      0       8
3       150                    1       100

I'm not sure how to best arrange the data in STATA since I'm confused as to
how to put this data in the wide-person format since I don't have an Event1,
Event2, Event3 or a Wait1 Wait2 Wait3..  I have tried creating a vector
using loop commands (to give me an Event1 Event2
Event3) but I need to specify the number of variables I create (max
390 days of observation) and this is different for each patient..

Any help or steps in the right direction would be appreciated! Thank you

Kyleigh
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