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adjelev
2007 Oct 11
0
Cox with time varying effect
...448 present normal
my first model without time varying hr is:
> mod<-coxph(Surv(time,status)~age_diag+deep+ldh,data=dtemp)
> mod
coef exp(coef) se(coef) z p
age_diag 0.0374 1.04 0.0124 3.03 0.0025
deeppresent 0.8639 2.37 0.3012 2.87 0.0041
ldhelevated 0.7222 2.06 0.2836 2.55 0.0110
Likelihood ratio test=21 on 3 df, p=0.000105 n= 91
To fit time dependent model, I used the survSplit() function to format dtemp into count data format:
> cdf<-survSplit(
cut=1:213, #cut at each month (last time is 213.9)...