There is however the generic vcov(), which has a method for class
"survreg".
One good reason for not having a simple means to extract standard
errors is that considering coefficients in isolation is often unwise
(and has come up on R-help more than once already this month).
The summary() method for class "survreg", like many other
model-fitting functions, has an argument 'correlation'. In the mid
1990s for S(-PLUS) the default for this argument was usually true. I
can see why the R tradition changed to false, but reminding people of
the correlation matrix when printing the coefficient table had merit.
On Sat, 14 May 2011, David Winsemius wrote:
On May 14, 2011, at 5:48 AM, andre bedon wrote:
Hi,Just a quick one, does anyone know the command for accessing the
standard errors from a survreg object? I can access the coefficients by
model$coefficients, but I cant seem to find a command to access the errors.
Any help would be greatly appreciated.Regards,Andre
I do not see an se.coef extractor function in the help pages for survreg or
survreg.object, so I guess you need to make one:
fit <- survreg(Surv(futime, fustat) ~ ecog.ps + rx, ovarian, dist='weibull',
scale=1)
Two methods seem to be equivalent on the first example in help(survreg):
summary(fit)$table[ , "Std. Error"]
(Intercept) ecog.ps rx
1.3218774 0.5869936 0.5869936
sqrt(diag(fit$var))
(Intercept) ecog.ps rx
1.3218774 0.5869936 0.5869936
The first one is preferred because after looking at the summary.survreg
function, one sees that it first checks for other conditions that were
recorded in the fit object and only if those are met does it apply the second
method, and it further checks to see if robust errors had been requested.
There can be some risk in creating your own extraction methods, since the
author of a package may have had reasons for not making it available, but in
this case he did offer a table that includes the component you were
requesting.
David Winsemius, MD
West Hartford, CT
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--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
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