On Thu, 18 May 2006, [EMAIL PROTECTED] wrote:
> Full_Name: Ben Fitzpatrick
> Version: 2.3.0
> OS: Windows XP and Mac OSX
> Submission from: (NULL) (160.36.15.155)
>
>
> When you fit a linear model (lm) and use the summary command, the assessment
> of
> the statistical significance of explanatory variables is very different than
> if
> you use the anova command. The F statistics calculated by anova are much
> larger
> than what you get out of SAS, for example. I think R is not calculating F
> statistics correctly.
The anova() function is not supposed to give the same results as
summary().
You don't say *which* SAS results it is "much larger" than (or even
provide a single example), but if you mean the most common SAS anova table
based on "Type III SS" then (a) the anova() results are not supposed to be
the same and (b) it is not true that they are always "much larger". They
can be the same or (much) smaller.
If you had read the FAQ you would at least know that the anova() output
was not supposed to be the same as that from SAS. You could then have
either asked why it was different or asked how to get the output you
wanted.
If R were really giving completely wrong answers for a very simple and
widely used analysis and no-one had noticed, an example would still have
been needed to make this a useful bug report.
-thomas
______________________________________________
R-devel@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-devel
