--------------------------------------------------------------------------------
Calrification
Am using stata 8
This is what my data looks like
Id sex date_visit age failure
1 0 04jun2004 28 0
1 0 12jun2004 28 0
1 0 18jun2004 28 0
1 0 16jul2004 29 0
1 0 13aug2004 30 0
2 0 01mar2002 0 0
2 0 27mar2002 1 0
2 0 15apr2002 2 0
2 0 18apr2002 2 1
2 0 29apr2002 2 0
basic time scale is calender time declared on the stset
origin and scale control the mapping from the basic time scale onto the
time scale on which the analysis is to be performed
.
. stset date_visit, id (rsv) failure(lrti) enter(time
date_origin)origin(time d(31jan2002)) exit(time date_exit) scale(1)
id: rsv
failure event: lrti != 0 & lrti < .
obs. time interval: (date_visit[_n-1], date_visit]
enter on or after: time date_origin
exit on or before: time date_exit
t for analysis: (time-origin)
origin: time d(31jan2002)
------------------------------------------------------------------------------
29979 total obs.
0 exclusions
------------------------------------------------------------------------------
29979 obs. remaining, representing
469 subjects
952 failures in multiple failure-per-subject data
377180 total analysis time at risk, at risk from t = 0
earliest observed entry t = 0
last observed exit t = 1177
. **** Checking the goodness of fit of the final model
. * evaluated by using Cox-Snell residuals
. * if the model fits the data well then the true cumulative hazard
function conditional on the covariate vector should have an exponential
distribution with a hazard rate of one
. quietly xi: stcox i.currentagegrp sex i.siblings_un6 i.main_fuel
i.hse_toilet i.babies_bor i.education i.family_children
i.interaction_un6 i.siblingssch_un6 i.siblingsroom_ov6 i.female_sibs
poor i.weaning i.job_desc, nohr mgale(mg)
. * compute cox-snell residuals
. predict cs, csnell
(663 missing values generated)
. *re stset using cs residuals as the time variable (look at the output)
the missing values are truly missing but it is omitting some of the
observations ????? It is also assuming single failure single record
which is incorrect as shown above my data set has multiple records
multiple failure-per-subject data.
. stset cs, failure(lrti)
failure event: lrti != 0 & lrti < .
obs. time interval: (0, cs]
exit on or before: failure
------------------------------------------------------------------------------
29979 total obs.
663 event time missing (cs>=.) PROBABLE
ERROR
1046 obs. end on or before enter()
------------------------------------------------------------------------------
28270 obs. remaining, representing
925 failures in single record/single failure data
925 total analysis time at risk, at risk from t = 0
earliest observed entry t = 0
last observed exit t = .8936376
Does anyone know how cs residuals are computed in this kind of data and
how I can specify multiple failure multiple recors when using cs
residuals as the time variable
Thank you
Emelda Okiro
Centre for Geographic Medicine Research - Coast
Kemri/Wellcome Trust Research Programme
P. O. Box 230
Kilifi, Kenya
Tel +254 41 522063/552535/525043
Fax +254 41 522390
>>> [email protected] 05/30/06 13:30 PM >>>
I don't know much about -stcox-. But I guess the main
reason you got no replies is that there is absolutely
no information here on what error messages you got
and which command triggered it.
Also, the FAQ explains that the current version of Stata is 9.2
and that you should state if you are using another version.
Your use of the -graph- command suggests to me that
you are _not_ using 9.2. (If you are using Stata >= 8, then
the -graph- command here will not work, and needs to be
in terms of -graph7-.)
Finally, this section of the FAQ is relevant:
4. What to do if you do not get an answer
http://www.stata.com/support/faqs/res/statalist.html#noanswer
Nick
[email protected]
Emelda Okiro
> I posted this message last week and i have not got a response so i
> thought it wise to maybe try my luck again
>
> I am trying to assess the goodness of fit of my cox Model using the
> cox-snell residuals but am getting
> an error message. I have a dataset with repeated measurement within
> individuals. The model has several variables with more than two
> categories. I am using calender time as my analysis time scale as
> exposure varies with time. I think its something to do with the way i
> have set my data. Can anyone please assist me. i have
> included my stata
> code.
>
> I first stset my data using
> stset date_visit, id (rsv) failure(lrti) enter(time
> date_origin)origin(time d(31jan2002)) exit(time date_exit) scale(1)
>
>
> quietly xi: stcox i.currentagegrp sex i.siblings_un6 i.main_fuel
> i.hse_toilet i.babies_bor i.education i.family_children
> i.interaction_un6 i.siblingssch_un6 i.siblingsroom_ov6 i.female_sibs
> poor i.weaning i.job_desc, nohr mgale(mg)
>
> predict cs, csnell
>
> stset cs, failure(lrti)
>
> sts gen H=na
>
> graph H cs cs, c(ll) s(o.) sort xlab(0 1 to 10) ylab(0 1 to 10)
>
*
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