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st: weighted time dependent Cox model


From   Ehsan Karim <ehsan.karim@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: weighted time dependent Cox model
Date   Sat, 18 Feb 2012 15:07:00 -0800

Dear Stata list,

I am trying to reproduce the weighted time dependent Cox model
(Andersen–Gill format with IPTW) results in Stata that are originally
obtained from R using same dataset, but so far getting the estimates
different. Could anyone indicate what I could be done to fix this?

Any suggestions/references will be highly appreciated.

Thanks,

Ehsan



##########################################
# R results: coef -0.288 se 0.174
##########################################

> dataset = read.csv("http://stat.ubc.ca/~e.karim/dataset.csv";)
> msmc = coxph(Surv(enter, exit, event) ~ tx + cluster(id), robust = TRUE, data = dataset, weights = weight)
> summary(msmc)
  n= 14372, number of events= 131

      coef exp(coef) se(coef) robust se      z Pr(>|z|)
tx -0.2882    0.7496   0.1745    0.1964 -1.467    0.142

   exp(coef) exp(-coef) lower .95 upper .95
tx    0.7496      1.334    0.5101     1.102

Concordance= 0.534  (se = 0.021 )
Rsquare= 0   (max possible= 0.136 )
Likelihood ratio test= 2.8  on 1 df,   p=0.09455
Wald test            = 2.15  on 1 df,   p=0.1423
Score (logrank) test = 2.75  on 1 df,   p=0.09739,   Robust = 2.11  p=0.1459

##########################################
# Stata results: coef -.605 se .643
##########################################

. use http://stat.ubc.ca/~e.karim/dataset, clear
(6 vars, 14372 obs)
. stset exit [pweight=weight], fail(event) exit(exit) id(id) enter(enter)
                id:  id
     failure event:  event != 0 & event < .
obs. time interval:  (exit[_n-1], exit]
 enter on or after:  time enter
 exit on or before:  time exit
            weight:  [pweight=weight]
------------------------------------------------------------------------------
    14372  total obs.
    12872  obs. begin on or after exit
------------------------------------------------------------------------------
     1500  obs. remaining, representing
     1500  subjects
       17  failures in single failure-per-subject data
     1500  total analysis time at risk, at risk from t =         0
                             earliest observed entry t =         0
                                  last observed exit t =         1

. stcox tx, nohr robust nolog
         failure _d:  event
   analysis time _t:  exit
  enter on or after:  time enter
  exit on or before:  time exit
                 id:  id
             weight:  [pweight=weight]
(sum of wgt is   1.5062e+03)

Cox regression -- Breslow method for ties

No. of subjects      =  1506.227846                Number of obs   =      1500
No. of failures      =  17.16531456
Time at risk         =  1506.227846
                                                   Wald chi2(1)    =      0.89
Log pseudolikelihood =   -124.48415                Prob > chi2     =    0.3464

                                  (Std. Err. adjusted for 1500 clusters in id)
------------------------------------------------------------------------------
             |               Robust
          _t |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
          tx |  -.6053404   .6428669    -0.94   0.346    -1.865336    .6546555
------------------------------------------------------------------------------

##########################################
# dataset (partial)
##########################################
. list
       +-------------------------------------------------------------------+
       |   id   tx   event   enter   exit     weight   _st   _d   _t   _t0 |
       |-------------------------------------------------------------------|
    1. |    1    0       0       0      1   1.356058     1    0    1     0 |
    2. |    1    0       0       1      2   1.356058     0    .    .     . |
    3. |    1    0       0       2      3   1.356058     0    .    .     . |
    4. |    1    1       0       3      4   1.356058     0    .    .     . |
    5. |    1    0       0       4      5   1.356058     0    .    .     . |
    6. |    1    0       0       5      6   1.356058     0    .    .     . |
    7. |    1    0       0       6      7   1.356058     0    .    .     . |
    8. |    1    0       0       7      8   1.356058     0    .    .     . |
    9. |    1    0       0       8      9   1.356058     0    .    .     . |
   10. |    1    1       0       9     10   1.356058     0    .    .     . |
       |-------------------------------------------------------------------|
   11. |    2    0       0       0      1    1.57168     1    0    1     0 |
   12. |    2    0       0       1      2    1.57168     0    .    .     . |
   13. |    2    1       0       2      3    1.57168     0    .    .     . |
   14. |    2    0       0       3      4    1.57168     0    .    .     . |
   15. |    2    1       0       4      5    1.57168     0    .    .     . |
   16. |    2    1       0       5      6    1.57168     0    .    .     . |
   17. |    2    1       0       6      7    1.57168     0    .    .     . |
   18. |    2    0       0       7      8    1.57168     0    .    .     . |
   19. |    2    0       0       8      9    1.57168     0    .    .     . |
   20. |    2    0       0       9     10    1.57168     0    .    .     . |
       |-------------------------------------------------------------------|
   21. |    3    0       0       0      1    .983771     1    0    1     0 |
   22. |    3    0       0       1      2    .983771     0    .    .     . |
   23. |    3    0       0       2      3    .983771     0    .    .     . |
   24. |    3    0       0       3      4    .983771     0    .    .     . |
   25. |    3    1       0       4      5    .983771     0    .    .     . |
   26. |    3    0       0       5      6    .983771     0    .    .     . |
   27. |    3    0       0       6      7    .983771     0    .    .     . |
   28. |    3    0       0       7      8    .983771     0    .    .     . |
   29. |    3    1       0       8      9    .983771     0    .    .     . |
   30. |    3    0       0       9     10    .983771     0    .    .     . |
--more--

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