On 7/12/07, Terry Therneau <[EMAIL PROTECTED]> wrote:
> The question was how to get the p-value from the fit below, as an S object
>
> sr<-survreg(s~groups, dist="gaussian")
> Coefficients:
> (Intercept)      groups
> -0.02138485  0.03868351
>
> Scale= 0.01789372
>
> Loglik(model)= 31.1   Loglik(intercept only)= 25.4
>         Chisq= 11.39 on 1 degrees of freedom, p= 0.00074
> n= 16
>
>
> ----
>   In general, good places to start are
>     > names(sr)
>     > help(survreg.object)
>     > ssr <- summary(sr)
>     > names(ssr)
> As someone else pointed out, it's also easy to look at the print.survreg
> function and see how the value was created -- one of the things I love
> about S.
>
> Unfortunately, doing the above myself showed that I have let the documentation
> page for survreg.object get seriously out of date -- quite embarassing as
> that is logically the first place to start.
>
> As to the print function creating things "on the fly": there is an area where
> there is no good answer.  Does one make the return object from a fit such
> that it contains only minimal data, or add in all of the other computations
> that can be derived from these?  The Chambers and Hastie book "Statistical
> Models in S", which was the starting point for model objects, leaned towards
> the former, and this still influences many functions.  Often the summary
> function will "fill in" these derived values, the std and t-tests for
> the individual coefficients for instance.

I think this is where it's nice to have a separate function that does
the filling in - then you can have the best of both worlds.  That's
the role that summary often plays.

Hadley

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