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st: Fw: R, STATA clogit


From   Richard Beckett <[email protected]>
To   "[email protected]" <[email protected]>
Subject   st: Fw: R, STATA clogit
Date   Fri, 7 Jun 2013 10:19:41 -0700 (PDT)

This question requires some finesse in both R and STATA so hopefully I will be able to get an answer here. I am much more adept in R and am trying to replicate the results of a STATA file in R.

This is the code for the clogit in STATA
clogit sftpcons sftptv2a3 sftptv2a4 sftptv2a5 sftptv2a2 sftptv2a6 logim maccat disp4cat if sample==1 & glb_ind=="Y", group(stratida)
and I tried to replicate it using
clogit1<-clogit(sftpcons~sftptv2a3+sftptv2a4+sftptv2a5+sftptv2a2+sftptv2a6+logim+maccat+disp4cat+strata(stratida), dframe, sample==1 | glb_ind=="Y")
but got different results
What did I do wrong here? I interpreted the STATA clogit as run this logit as long as the sample is 1 and glb_ind="Y" What should I be doing instead?

Here is the R output:

Call:
coxph(formula = Surv(rep(1, 1404L), sftpcons) ~ sftptv2a3 + sftptv2a4 + 
    sftptv2a5 + sftptv2a2 + sftptv2a6 + logim + maccat + disp4cat + 
    strata(stratida), data = dframe, method = "exact")

  n= 1404, number of events= 351 

             coef           exp(coef) se(coef)      z Pr(>|z|)    
sftptv2a3  1.4552    4.2852   0.2273  6.401 1.54e-10 ***
sftptv2a4  3.1118   22.4609   0.2265 13.739  < 2e-16 ***
sftptv2a5  1.0717    2.9204   0.2522  4.249 2.15e-05 ***
sftptv2a2  0.7185    2.0514   0.3300  2.177   0.0295 *  
sftptv2a6  2.7341   15.3965   0.5050  5.414 6.17e-08 ***
logim      0.7579    2.1338   0.1347  5.625 1.85e-08 ***
maccat     3.0809   21.7771   0.4005  7.693 1.43e-14 ***
disp4cat   0.7061    2.0261   0.1524  4.634 3.59e-06 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

                   exp(coef) exp(-coef) lower .95 upper .95
sftptv2a3     4.285    0.23336     2.745     6.691
sftptv2a4    22.461    0.04452    14.409    35.013
sftptv2a5     2.920    0.34241     1.781     4.788
sftptv2a2     2.051    0.48747     1.074     3.917
sftptv2a6    15.397    0.06495     5.722    41.429
logim         2.134    0.46866     1.639     2.779
maccat       21.777    0.04592     9.934    47.739
disp4cat      2.026    0.49355     1.503     2.731

Rsquare= 0.239   (max possible= 0.623 )
Likelihood ratio test= 383.2  on 8 df,   p=0
Wald test            = 264.7  on 8 df,   p=0
Score (logrank) test = 396.2  on 8 df,   p=0


And the STATA output:

Iteration 0:   log likelihood = -95.537697  
Iteration 1:   log likelihood = -91.465581  
Iteration 2:   log likelihood = -91.402366  
Iteration 3:   log likelihood = -91.402264  
Iteration 4:   log likelihood = -91.402264  

Conditional (fixed-effects) logistic regression   Number of obs   =        468
                                                  LR chi2(8)      =     141.59
                                                  Prob > chi2     =     0.0000
Log likelihood = -91.402264                       Pseudo R2       =     0.4365

------------------------------------------------------------------------------
    sftpcons |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   sftptv2a3 |   2.042827   .4741327     4.31   0.000     1.113544     2.97211
   sftptv2a4 |    4.10828   .5593723     7.34   0.000      3.01193    5.204629
   sftptv2a5 |   1.766492   .5585173     3.16   0.002     .6718177    2.861165
   sftptv2a2 |   1.366568   .6540307     2.09   0.037      .084691    2.648444
   sftptv2a6 |   2.307152   .8225835     2.80   0.005     .6949178    3.919386
       logim |   1.404135   .3480976     4.03   0.000     .7218764    2.086394
      maccat |     2.8423   .7008588     4.06   0.000     1.468642    4.215958
    disp4cat |   .6347805   .2872258     2.21   0.027     .0718283    1.197733
------------------------------------------------------------------------------

Also tried changing method=approximate with no noticeable change 

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