On Fri, Oct 1, 2010 at 10:33 AM, T. Smithson <pillepop2...@yahoo.de> wrote:
> Dear R-community,
>
> I have a short question: How do I interpret the result of a
> likelihood ratio test correctly?
It compares two nested models. A small (enough) p-value indicates that
you should reject the simpler explanation (in this case the Null
model).
> I am fitting a parametric survival model (with aftreg {eha}) and the
> output tells me the overall p-value of my model is < 0.001. .My
> simple question is: Does the result mean my model fits the data well
> OR does it mean my model DOES NOT fit the data well?
No.
>
> Some side information how the p-value is calculated:
>
> logtest <- -2 * (x$loglik[1] - x$loglik[2])
> pvalue <- 1-pchisq(logtest,df)
>
> with
> x$loglik[1] = -274
> x$loglik[2] = -235
> df = 25
>
> I know the answer would probably be "read the manual" but I found
> different opinions on the web and want to make sure I am
> interpreting it correctly.
>
> Thanks
> Thomas
>
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--
Göran Broström
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