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R: R: st: R: Someone help me on the multiple failure duration model?


From   "Carlo Lazzaro" <carlo.lazzaro@tiscalinet.it>
To   <statalist@hsphsun2.harvard.edu>
Subject   R: R: st: R: Someone help me on the multiple failure duration model?
Date   Tue, 4 Nov 2008 09:32:43 +0100

Dear Martin,
You're most welcome!

As an addition to my yesterday's reply and related references (included the ones pointed out by Jose Maria Pacheco de Souza), I would kindly recommend you to take a thorough look  Stata Manual [ST] Survival Analysis and Epidemiological Tables (my release is 9).

Kind Regards and All the Best for your research project,

Carlo

-----Messaggio originale-----
Da: Martin Wang [mailto:zwang215@gmail.com] 
Inviato: lunedì 3 novembre 2008 19.17
A: Carlo Lazzaro
Oggetto: Re: R: st: R: Someone help me on the multiple failure duration model?

Dear Carlo,

Many thanks indeed that you even tried to test the data! Your asnwer definitely helps a lot! From your procedure I have a basic idea of how to deal with such problems. I'd like to reconfirm one thing, that is, you see from my data, the key variable - health state, in some year did not change from the last year but the control variable (weight) changed. I'd like to make sure that there is no problem if I use all the observations (which I think is 18 observations in total). 

Many thanks again! 

Best,

Martin

======= 2008-11-04 01:43:04 Original Message:=======

>Dear Martin, 
>I tried to load the excerpt of the data set provided in your previous message. Whereas Cox proportional hazard model seems to hold (please, see -estat phtest-), the Gamma generalized regression for finding which parametric survival model fits best with your data, doesn't converge (please, see the error message).
>
>stset year, id(id) failure(health_state==1) exit(time .) scale(1)
>
>                id:  id
>     failure event:  health_state == 1
>obs. time interval:  (year[_n-1], year]
> exit on or before:  time .
>
>------------------------------------------------------------------------------
>       21  total obs.
>        0  exclusions
>------------------------------------------------------------------------------
>       21  obs. remaining, representing
>        3  subjects
>        6  failures in multiple failure-per-subject data
>       21  total analysis time at risk, at risk from t =         0
>                             earliest observed entry t =         0
>                                  last observed exit t =         7
>
>stcox female weight, schoenfeld(sch*)
>
>         failure _d:  health_state == 1
>   analysis time _t:  year
>  exit on or before:  time .
>                 id:  id
>
>Iteration 0:   log likelihood = -5.7807435
>Iteration 1:   log likelihood = -4.7542542
>Iteration 2:   log likelihood = -4.7462302
>Iteration 3:   log likelihood =  -4.746223
>Refining estimates:
>Iteration 0:   log likelihood =  -4.746223
>
>Cox regression -- no ties
>
>No. of subjects =            3                     Number of obs   =        18
>No. of failures =            6
>Time at risk    =           18
>                                                   LR chi2(2)      =      2.07
>Log likelihood  =    -4.746223                     Prob > chi2     =    0.3554
>
>------------------------------------------------------------------------------
>          _t | Haz. Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
>-------------+----------------------------------------------------------------
>      female |   .2556673   .3192123    -1.09   0.275     .0221264    2.954196
>      weight |   1.079909   .0695928     1.19   0.233     .9517721    1.225297
>------------------------------------------------------------------------------
>
>. estat phtest
>
>      Test of proportional hazards assumption
>
>      Time:  Time
>      ----------------------------------------------------------------
>                  |                      chi2       df       Prob>chi2
>      ------------+---------------------------------------------------
>      global test |                      2.77        2         0.2505
>      ----------------------------------------------------------------
>
>streg female weight, dist(gamma)
>
>         failure _d:  health_state == 1
>   analysis time _t:  year
>  exit on or before:  time .
>                 id:  id
><output omitted>
>discontinuous region encountered
>cannot compute an improvement
>r(430);
>
>I cannot rule out the occurrence of some mistakes in my tackling the issues you outlined.
>
>I do hope that it (at least a bit) help.
>
>Kind Regards,
>Carlo
>-----Messaggio originale-----
>Da: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Martin Wang
>Inviato: lunedì 3 novembre 2008 17.03
>A: statalist@hsphsun2.harvard.edu; statalist@hsphsun2.harvard.edu
>Oggetto: Re: st: R: Someone help me on the multiple failure duration model?
>
>Dear Carlo,
>
>Many thanks for your suggestion. I've just requested the book from other library. But my question is a little bit urgent, if anyone happens to know the answer could you please kindly help.
>
>Thanks!
>
>Martin
>
>======= 2008-11-03 23:40:52 Original Message:=======
>
>>Dear Martin,
>>all these topics are covered in Cleves MA, Gould WW, Gutierrez RG. An
>>introduction to survival analysis using Stata. Revised edition. College
>>Station: Stata Press, 2004.
>>
>>In my opinion, this is a very "good value for money" textbook.
>>
>> 
>>Kind Regards,
>>
>>Carlo
>>-----Messaggio originale-----
>>Da: owner-statalist@hsphsun2.harvard.edu
>>[mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Martin Wang
>>Inviato: luned?3 novembre 2008 16.22
>>A: statalist@hsphsun2.harvard.edu
>>Oggetto: st: Someone help me on the multiple failure duration model?
>>
>>/********** This is a html email************************/
>>
>>Dear all, 
>>
>>Can someone help me on the multiple failure duration model? For example,
>>let's say I have the following data:
>>
>>
>>year             |       1        |         2        |        3         |
>>4         |       5          |       6         |      7                  
>>patient 1(Female)|weight:50,ill(0)| weight:52,ill(0) |
>>weight:53,fine(1)|weight:48,fine(1)|weight:50,ill(0)  |weight:50,ill(0)
>>|weight:50,ill(0)
>>patient 2(male)  |weight:51,ill(0)| weight:48,ill(0) | weight:60,ill(0) |
>>weight:67,ill(0)|weight:78,fine(1) |weight:60,fine(1)| (missing)  
>>patient 3(male)  |weight:52,ill(0)| weight:50,fine(1)| (missing)        |
>>(missing)       | weight:50,fine(1)| weight:40,ill(0)| weight:60,ill(0) 
>>
>>
>>You see for each patient there are multiple observations, and also there may
>>be multiple failures(in this case - getting fine). And also some subject has
>>gap in the data, for example patient 3 has gap in year 3 and year 4. I
>>wonder whether I can still use streg or stcox for this setting and use ALL
>>the observations. For example,
>>
>>*****************************************************
>>stset t, id(patient) failure(fine) exit(time .) noshow
>>stcox weight female, r 
>>or streg weight female, r
>>*****************************************************
>>Can anyone kindly help me out? Any suggestions?
>>
>>Many thanks!!
>>
>>Martin
>>
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