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When performing the same cox-regression in SAS and i R (including and interaction with a 3 knot restricted cubic spline), I receive different parameter estimates (i.e on age_spline 2). In my example below I have used the dataset=WHAS500 found on this website (https://stats.idre.ucla.edu/sas/seminars/sas-survival/)

To harmonize the models (and the splines) between SAS and R I have used knots according to Harrell's scheme (https://blogs.sas.com/content/iml/2019/02/18/regression-restricted-cubic-splines-sas.html) and set both TIES to EFRON

SAS-code

proc phreg data = whas500;
effect age_spline = spline(age/ details naturalcubic basis=tpf(noint) 
knotmethod=percentilelist(10 50 90));
model lenfol*fstat(0) = gender|age_spline /rl ties=EFRON; 
run;

R-code

fit <- cph(Surv(LENFOL, FSTAT) ~ GENDER*rcs(AGE,3), data = whas500)

Output

enter image description here

I would be very thankful if someone can help me explain the observed differences.

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    $\begingroup$ Did you notice that although two of the coefficient estimates differ, they nevertheless have identical p-values in both programs? This implies there's simply a difference in how the terms are standardized. It's unlikely the R documentation explains this, so consider comparing the model matrices in both programs. $\endgroup$
    – whuber ♦
    Commented Jul 31, 2020 at 16:11
  • 1
    $\begingroup$ Thank you for the suggestion! $\endgroup$
    – Thomas
    Commented Aug 10, 2020 at 13:21

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