On Nov 13, 2010, at 12:51 PM, Biau David wrote:
Dear R help list,
I am modeling some survival data with coxph and survreg
(dist='weibull') using
package survival. I have 2 problems:
1) I do not understand how to interpret the regression coefficients
in the
survreg output and it is not clear, for me, from ?survreg.objects
how to.
Have you read:
?survreg.distributions # linked from survreg help
Here is an example of the codes that points out my problem:
- data is stc1
- the factor is dichotomous with 'low' and 'high' categories
Not an unambiguous description for the purposes of answering your many
questions. Please provide data or at the very least: str(stc1)
slr <- Surv(stc1$ti_lr, stc1$ev_lr==1)
mca <- coxph(slr~as.factor(grade2=='high'), data=stc1)
Not sure what that would be returning since we do not know the
encoding of grade2. If you want an estimate on a subset wouldn't you
do the subsetting outside of the formula? (You may be reversing the
order by offering a logical test for grade2.)
mcb <- coxph(slr~as.factor(grade2), data=stc1)
You have not provided the data or str(stc1), so it is entirely
possible that as.factor is superfluous in this call.
mwa <- survreg(slr~as.factor(grade2=='high'), data=stc1,
dist='weibull',
scale=0)
mwb <- survreg(slr~as.factor(grade2), data=stc1, dist='weibull',
scale=0)
summary(mca)$coef
coef
exp(coef) se(coef) z Pr(>|z|)
as.factor(grade2 == "high")TRUE 0.2416562 1.273356 0.2456232
0.9838494 0.3251896
summary(mcb)$coef
coef exp(coef)
se(coef) z Pr(>|z|)
as.factor(grade2)low -0.2416562 0.7853261 0.2456232 -0.9838494
0.3251896
summary(mwa)$coef
(Intercept) as.factor(grade2 == "high")TRUE
7.9068380 -0.4035245
summary(mwb)$coef
(Intercept) as.factor(grade2)low
7.5033135 0.4035245
No problem with the interpretation of the coefs in the cox model.
However, i do
not understand why
a) the coefficients in the survreg model are the opposite (negative
when the
other is positive) of what I have in the cox model? are these not
the log(HR)
given the categories of these variable?
Probably because the order of the factor got reversed when you changed
the covariate to logical and them back to factor.
b) how come the intercept coefficient changes (the scale parameter
does not
change)?
2) My second question relates to the first.
a) given a model from survreg, say mwa above, how should i do to
extract the
base hazard
Answered by Therneau earlier this week and the next question last month:
https://stat.ethz.ch/pipermail/r-help/2010-November/259570.html
https://stat.ethz.ch/pipermail/r-help/2010-October/257941.html
and the hazard of each patient given a set of predictors? With the
hazard function for the ith individual in the study given by h_i(t) =
exp(\beta'x_i)*\lambda*\gamma*t^{\gamma-1}, it doesn't look like to
me that
predict(mwa, type='linear') is \beta'x_i.
b) since I need the coefficient intercept from the model to obtain
the scale
parameter to obtain the base hazard function as defined in Collett
(h_0(t)=\lambda*\gamma*t^{\gamma-1}), I am concerned that this
coefficient
intercept changes depending on the reference level of the factor
entered in the
model. The change is very important when I have more than one
predictor in the
model.
Any help would be greatly appreciated,
David Biau.
David Winsemius, MD
West Hartford, CT
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