Hi,
Here is the summary-output of the Coxph-model I used (the output is based on
the best final model i.e. all significant explanatory variables and their
interactions are included):
coxph(formula = Y ~ LT + Food + Temp2 + LT:Food + LT:Temp2 +
Food:Temp2 + LT:Food:Temp2)
n= 555
coef exp(coef)
se(coef) z Pr(>|z|)
LT 9.302e+02 Inf 2.822e+02
3.297 0.000979 ***
Food 3.397e+03 Inf 1.023e+03
3.321 0.000896 ***
Temp2 5.016e+03 Inf 1.522e+03
3.296 0.000979 ***
LT:Food -2.250e+02 1.950e-98 6.807e+01 -3.305
0.000949 ***
LT:Temp2 -3.327e+02 3.352e-145 1.013e+02 -3.284
0.001022 **
Food:Temp2 -1.212e+03 0.000e+00 3.666e+02 -3.307
0.000942 ***
LT:Food:Temp2 8.046e+01 8.815e+34 2.442e+01 3.295
0.000986 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Rsquare= 0.123 (max possible= 0.858 )
Likelihood ratio test= 72.91 on 7 df, p=3.811e-13
Wald test = 55.79 on 7 df, p=1.042e-09
Score (logrank) test = 78.57 on 7 df, p=2.687e-14
Question is:
How to interpret coefficient and exp(coef) values in this case, as they are
very large values? Also 3-case interaction is involved, which confuses the
interpretation more.
All the examples concerning Coxph-model I have found so far online have been
really simple regarding the intercation terms (which have always turned out
to be unsignificant) and also coefficient-values (=hazard rates) and
exponentials of these (=hazard ratios) have been pretty small and "easy to
handle" numbers, e.g. coefficient = 1.73 -> exp(coef) = 5.64. BUT mine are
way bigger numbers as you can see from the summary output (above). And
because they are so large vaues, they almost seem to not make any sense.
Grateful for the help,
R-girl
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