Dear R users,
Here is the coxme output I obtain on my survival dataset having 3 strains
and 2 infection status (i: infected, ni: non infected)
coxme(Surv(lay) ~ infection*strain, data=datalay, random= ~1 |block)
Cox mixed-effects model fit by maximum likelihood
Data: datalay
n= 1194
Iterations= 3 77
NULL Integrated Penalized
Log-likelihood -7270.028 -7223.859 -7218.175
Penalized loglik: chisq= 103.71 on 10.24 degrees of freedom, p= 0
Integrated loglik: chisq= 92.34 on 6 degrees of freedom, p= 0
Fixed effects: Surv(lay) ~ infection * strain
coef exp(coef) se(coef) z
p
(line1) infection_ni -0.6482079 0.5229822
0.1481232 -4.38 1.2e-05
(line2) strainB -0.8797408
0.4148904 0.1091490 -8.06 7.8e-16
(line3) strainC -0.7378955
0.4781191 0.1045977 -7.05 1.7e-12
(line4 ) infection_ni:strainB 0.7631418
2.1450049 0.1462481 5.22 1.8e-07
(line5 ) infection_ni:strainC 0.5358302
1.7088664 0.1431092 3.74 1.8e-04
Random effects: ~1 | block
block
Variance: 0.02493629
I'm not sure I understand properly what are the hazard ratios in the
*exp(coef)
column* for the two interaction terms. In the R book of Mick Crawley is
explained that you should be able to calculate these figures approximatively
using the mean survival as below:
tapply(datalay$lay,datalay$strain:datalay$infection,mean)
A:i A:ni B:i B:ni
C:i C:ni
1.864865 2.888372 3.586826 3.253394 3.296296 3.52073
For example, the exp(coef) value in (line 1) of my model output
representsthe ratio between the mean survival of genotype A infected
(i), with mean
survival of genotype A (ni):1.86/2.88 = 0.64, not too far from what the
model gives.
Following the same reasoning, (line 2) is ratio between "B infected"
and "A
infected", and (line 3) the ratio between C (i) and A (i).
My question is very simple: *what are the hazard ratios for the interaction
terms stated (line 4) and (line 5), and how are they calculated ?*
Thanks a lot in advance,
Julien.
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