> What is the cumulative distribution (with parameterization) used within
> survreg with respect to the log-logistic distribution?
> That is, how are the parameters linked to the survivor function?
Reference: Kalbfleisch and Prentice, The statistical analysis of failure time
data, chapter 2. This is the basis for survreg.
Theory:
Let z = (log(time) - X beta)/ scale = the transformed data. Then
S(z) = 1/(1+exp(z)) = survival function.
Practice:
fit <- survreg(Surv(time, status) ~ ph.karno + age + sex, data=lung,
dist='loglogistic')
# Get the survival curve for a 60 year old male with Karnofsky score of 70
tdata <- data.frame(age=60, sex=1, ph.karno=70)
stemp <- 99:1/100
xtemp <- predict(fit, newdata=tdata, type='quantile', p=1-stemp)
plot(xtemp/365, stemp, xlab="Years", ylab='Survival', type='l')
I purposefully did not ask for the 0th percentile, which can cause problems
with
the logarithm, or the 100th percentile, which is infinite (and I'd like to keep
the plot to a reasonable scale).
Terry Therneau
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