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Re: st: Survival analysis question
From
Steven Samuels <[email protected]>
To
[email protected]
Subject
Re: st: Survival analysis question
Date
Wed, 3 Nov 2010 15:39:43 -0400
--
Al,
I don't think that the two times are consecutive: they are recorded as
seconds, but the the two observations on each subject were separated
by a week.
Steve
On Nov 3, 2010, at 2:50 PM, Feiveson, Alan H. (JSC-SK311) wrote:
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: [email protected] [mailto:[email protected]
] On Behalf Of Steven Samuels
Sent: Wednesday, November 03, 2010 12:35 PM
To: [email protected]
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
[email protected]
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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