On Wed, 5 Jul 2006, Celso Barros wrote:

> Dear All,
>
> When I run rlm to obtain robust standard errors, my output does not include
> p-values. Is there any reason p-values should not be used in this case? Is
> there an argument I could use in rlm so that the output does
> include p-values?

First you would have to derive a reliable theory for the tests you want 
p-values for.  The t ratios are approximately normally distributed, but to 
quote realistic p-values you would need much more accurate distribtution 
theory.

For summary.lm we can use Student's t distribution and say the results are 
exact only under normality.  There is no analogue for summary.rlm.  Note 
that S does not quote p-values for summmary.glm for similar reasons: R 
does but I do not consider it to be a good idea.

>
> Thanks in advance,
>
> Celso
>
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>
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-- 
Brian D. Ripley,                  [EMAIL PROTECTED]
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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