i.e., averaged across the levels of B)
> are the same. One can test this hypothesis whether or not A and B interact,
> since the marginal means can be formed whether or not the profiles of means
> for A within levels of B are parallel. Whether the hypothesis is of interest
> in the presence of interaction is another matter, however. To compute
> Type-III tests using incremental F-tests, one needs contrasts that are
> orthogonal in the row-basis of the model matrix. In R, this means, e.g.,
> using contr.sum, contr.helmert, or contr.poly (all of which will give you
> the same SS), but not contr.treatment. Failing to be careful here will
> result in testing hypotheses that are not reasonably construed, e.g., as
> hypotheses concerning main effects.
>
> (5) The same considerations apply to linear models that include quantitative
> predictors -- e.g., ANCOVA. Most software will not automatically produce
> sensible Type-III tests, however.
>
> I hope this helps,
> John
>
> --------
> John Fox
> Department of Sociology
> McMaster University
> Hamilton, Ontario
> Canada L8S 4M4
> 905-525-9140x23604
> http://socserv.mcmaster.ca/jfox
>
>
> > -Original Message-
> > From: [EMAIL PROTECTED]
> > [mailto:[EMAIL PROTECTED] On Behalf Of Amasco
> > Miralisus
> > Sent: Saturday, August 26, 2006 5:07 PM
> > To: r-help@stat.math.ethz.ch
> > Subject: [R] Type II and III sum of square in Anova (R, car package)
> >
> > Hello everybody,
> >
> > I have some questions on ANOVA in general and on ANOVA in R
> > particularly.
> > I am not Statistician, therefore I would be very appreciated
> > if you answer it in a simple way.
> >
> > 1. First of all, more general question. Standard anova()
> > function for lm() or aov() models in R implements Type I sum
> > of squares (sequential), which is not well suited for
> > unbalanced ANOVA. Therefore it is better to use
> > Anova() function from car package, which was programmed by
> > John Fox to use Type II and Type III sum of squares. Did I
> > get the point?
> >
> > 2. Now more specific question. Type II sum of squares is not
> > well suited for unbalanced ANOVA designs too (as stated in
> > STATISTICA help), therefore the general rule of thumb is to
> > use Anova() function using Type II SS only for balanced ANOVA
> > and Anova() function using Type III SS for unbalanced ANOVA?
> > Is this correct interpretation?
> >
> > 3. I have found a post from John Fox in which he wrote that
> > Type III SS could be misleading in case someone use some
> > contrasts. What is this about?
> > Could you please advice, when it is appropriate to use Type
> > II and when Type III SS? I do not use contrasts for
> > comparisons, just general ANOVA with subsequent Tukey
> > post-hoc comparisons.
> >
> > Thank you in advance,
> > Amasco
> >
> > [[alternative HTML version deleted]]
> >
> > __
> > R-help@stat.math.ethz.ch mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> > http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>
>
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