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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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