RE: st: Survival analysis question

["Feiveson, Alan H. (JSC-SK311)" <alan.h.feiveson@nasa.gov>]

Steve - In my opinion this is multiple failure data. Each subject is subjected to two consecutive exposures, and a subject can "fail" on none, either, or both of these tests. So the variable ttrxt at a given observation is the total time that the particular subject has been at risk up through that observation. Therefore I think the stset command 

. stset ttrxt, id(id) failure(fail) exit(time .)

                id:  id
     failure event:  fail != 0 & fail < .
obs. time interval:  (ttrxt[_n-1], ttrxt]
 exit on or before:  time .

------------------------------------------------------------------------------
       16  total obs.
        0  exclusions
------------------------------------------------------------------------------
       16  obs. remaining, representing
        8  subjects
       13  failures in multiple failure-per-subject data
     5607  total analysis time at risk, at risk from t =         0
                             earliest observed entry t =         0
                                  last observed exit t =      1198

is correct. I agree that ideally, one should try a frailty model on this data, but it doesn't work well with only 8 subjects.

Al Feiveson




-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Steven Samuels
Sent: Wednesday, November 03, 2010 12:35 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Survival analysis question


Chris Westby:


You don't have multiple-failure data, because the start time for the  
two tests should be zero. The correct statement is:

stset t, failure(fail)

This will change the -stcox- results as well. Also try -stsum,  
by(treatment)- after the two versions of -stset--.  I suggest that you  
consider the -shared-  option in -stcox- to allow for the possibility  
of person-specific baseline hazards. Note that eight subjects is  
probably not enough for the standard errors to be reliable.


Steve

Steven J. Samuels
sjsamuels@gmail.com
18 Cantine's Island
Saugerties NY 12477
USA
Voice: 845-246-0774
Fax:    206-202-4783


On Nov 3, 2010, at 8:35 AM, Westby, Christian Michael. (JSC-SK)[USRA]  
wrote:

Dear Statalisters,

I am working on comparing survival times in one group of subjects  
before and after treatment and am having a hard time with the "stset"  
code.


Using the following data set where testing was separated by 1 week, t  
is time of task before and after treatment (seconds) and ttrxt is time  
calculated to prevent time from being treated as continuous and fail  
is 0=completed, 1=not completed.



subjectid	treatment	fail			t	ttrxt
-----------------------------------------------------------------
1		pre		failed		169	169
1		post		failed		141	310
2		pre		failed		114	114
2		post		failed		84	198
3		pre		failed		564	564
3		post		failed		296	860
4		pre		failed		168	168
4		post		failed		332	500
5		pre		failed		215	215
5		post		failed		50	265
6		pre		completed		900	900
6		post		failed		196	1096
7		pre		completed		900	900
7		post		failed		298	1198
8		pre		completed		900	900
8		post		failed		280	1180
-----------------------------------------------------------------


I used


. stset ttrxt, id(subjectid) failure(fail) exit(time .)


id:  subjectid
failure event:  fail != 0 & fail < .
obs. time interval:  (ttrxt[_n-1], ttrxt]  exit on or before:  time .

------------------------------------------------------------------------------
       16  total obs.
        0  exclusions
------------------------------------------------------------------------------
       16  obs. remaining, representing
        8  subjects
       13  failures in multiple failure-per-subject data
     5607  total analysis time at risk, at risk from t =         0
                             earliest observed entry t =         0
                                  last observed exit t =      1198


I then ran


. stcox treatment, cluster(subjectid)

         failure _d:  fail
   analysis time _t:  ttrxt
  exit on or before:  time .
                 id:  subjectid

Iteration 0:   log pseudolikelihood = -20.175132
Iteration 1:   log pseudolikelihood = -18.079165
Iteration 2:   log pseudolikelihood = -18.026011
Iteration 3:   log pseudolikelihood = -18.025935
Refining estimates:
Iteration 0:   log pseudolikelihood = -18.025935

Cox regression -- no ties

No. of subjects      =            8                Number of obs    
=        16
No. of failures      =           13
Time at risk         =         5607
                                                   Wald chi2(1)     
=      4.22
Log pseudolikelihood =   -18.025935                Prob > chi2      
=    0.0399

                              (Std. Err. adjusted for 8 clusters in  
subjectid)
------------------------------------------------------------------------------
             |               Robust
          _t | Haz. Ratio   Std. Err.      z    P>|z|     [95% Conf.  
Interval]
-------------+----------------------------------------------------------
-------------+------
   treatment |   4.610013   3.428317     2.05   0.040     1.073226     
19.80218
------------------------------------------------------------------------------


I believe that the output and results are accurate however, I am  
unable to get Stata to correctly graph the survival curves using the  
following code



. stcurv, surv at1(treatment=0) at2(treatment=1)


the resulting graph incorrectly plots both groups starting at less  
than 100% at a time=0 and the x-axis scale is incorrect.


Any thoughts?



Chris


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