Dear GMM,

> -----Original Message-----
> From: Manzoni, GianMauro [mailto:gm.manz...@auxologico.it]
> Sent: July-30-12 9:49 AM
> To: John Fox
> Cc: r-help@r-project.org; Greg Snow
> Subject: Re: [R] MANOVA polynomial contrasts
> 
> Dear Prof. John Fox,
> thus all I should do to test quadratic and cubic effects is to change the
second
> argument of the linearHypothesis() function, right?
> So, for testing the cubic effect:
> >  linearHypothesis (mod, "f.C")

Yes, but wouldn't it have been faster simply to try it? Also see
?linearHypothesis.

> 
> Is there a chapter or paragragh about contrasts in your book "An R
> companion for applied regression"?

There are discussions of contrasts and of linear hypotheses about
coefficients, though not in the context of *multivariate* linear models;
that's the subject of an on-line appendix, at <
http://socserv.socsci.mcmaster.ca/jfox/Books/Companion/appendix/Appendix-Mul
tivariate-Linear-Models.pdf>.

Best,
 John

> 
> Best regards,
> GMM
> 
> 2012/7/30 John Fox <j...@mcmaster.ca>
> 
> 
>       Dear Gian Mauro,
> 
> 
>       On Mon, 30 Jul 2012 14:44:44 +0200
>        "Manzoni, GianMauro" <gm.manz...@auxologico.it> wrote:
>       > Dear Prof. John Fox,
>       > thank you very much for your suggestions.
>       > However, I still do not know how to use the contrasts after
> generating them.
>       > Once I generate the matrix with the polynomial contrasts, what are
> the
>       > following steps toward the statistical test?
> 
> 
>       Here's a contrived example, which uses the Anova() and
> linearHypothesis() functions in the car package:
> 
>       ----- snip ------
> 
>       > Y <- matrix(rnorm(300), 100, 3)
>       > colnames(Y) <- c("y1", "y2", "y3")
>       > f <- ordered(sample(letters[1:4], 100, replace=TRUE))
>       > (mod <- lm(Y ~ f))
> 
>       Call:
>       lm(formula = Y ~ f)
> 
>       Coefficients:
>                    y1        y2        y3
>       (Intercept)   0.06514  -0.01683  -0.13787
>       f.L          -0.37837   0.18309   0.29736
>       f.Q          -0.02102  -0.39894   0.08455
>       f.C           0.05898   0.09358  -0.17634
> 
>       > Anova(mod)
> 
>       Type II MANOVA Tests: Pillai test statistic
>         Df test stat approx F num Df den Df Pr(>F)
>       f  3   0.11395   1.2634      9    288 0.2566
> 
>       > linearHypothesis(mod, "f.L")
> 
>       Sum of squares and products for the hypothesis:
>                 y1        y2        y3
>       y1  3.607260 -1.745560 -2.834953
>       y2 -1.745560  0.844680  1.371839
>       y3 -2.834953  1.371839  2.227995
> 
>       Sum of squares and products for error:
>                 y1        y2        y3
>       y1 86.343376 -8.054928 -3.711756
>       y2 -8.054928 95.473020  2.429151
>       y3 -3.711756  2.429151 89.593163
> 
>       Multivariate Tests:
>                        Df test stat approx F num Df den Df   Pr(>F)
>       Pillai            1 0.0648520 2.172951      3     94 0.096362 .
>       Wilks             1 0.9351480 2.172951      3     94 0.096362 .
>       Hotelling-Lawley  1 0.0693495 2.172951      3     94 0.096362 .
>       Roy               1 0.0693495 2.172951      3     94 0.096362 .
>       ---
>       Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> 
>       ----- snip ------
> 
>       You could do similar tests for the quadratic and cubic contrasts.
> 
>       I hope this helps,
> 
>        John
> 
>       ------------------------------------------------
>       John Fox
>       Sen. William McMaster Prof. of Social Statistics
>       Department of Sociology
>       McMaster University
>       Hamilton, Ontario, Canada
>       http://socserv.mcmaster.ca/jfox/
> 
>       >
>       > A whole example would be very useful.
>       >
>       > Thank you very much in advance!
>       >
>       > Best regards,
>       > Gian Mauro Manzoni
>       >
>       >
>       >
>       > 2012/7/25 John Fox <j...@mcmaster.ca>
>       >
>       > > Dear Gian,
>       > >
>       > > How contrasts are created by default is controlled by the
> contrasts option:
>       > >
>       > > > getOption("contrasts")
>       > >         unordered           ordered
>       > > "contr.treatment"      "contr.poly"
>       > >
>       > > So, unless you've changed this option, contr.poly() will be used
to
>       > > generate orthogonal polynomial contrasts for an ordered factor,
> and you
>       > > therefore need do nothing special to get this result. For
example:
>       > >
>       > > > (f <- ordered(sample(letters[1:3], 10, replace=TRUE)))
>       > >  [1] c c a a c c b c a c
>       > > Levels: a < b < c
>       > >
>       > > > round(contrasts(f), 4)
>       > >           .L      .Q
>       > > [1,] -0.7071  0.4082
>       > > [2,]  0.0000 -0.8165
>       > > [3,]  0.7071  0.4082
>       > >
>       > > For more information, see section 11 on statistical models in
the
> manual
>       > > "An Introduction to R," which is part of the standard R
> distribution, and
>       > > in particular sections 11.1 and 11.1.1.
>       > >
>       > > I hope that this clarifies the issue.
>       > >
>       > > Best,
>       > >  John
>       > >
>       > > ------------------------------------------------
>       > > John Fox
>       > > Sen. William McMaster Prof. of Social Statistics
>       > > Department of Sociology
>       > > McMaster University
>       > > Hamilton, Ontario, Canada
>       > > http://socserv.mcmaster.ca/jfox/
>       > >
>       > > On Wed, 25 Jul 2012 11:58:30 +0200
>       > >  "Manzoni, GianMauro" <gm.manz...@auxologico.it> wrote:
>       > > > Dear Greg Snow,
>       > > > thank you very much for your suggestions. However, I need an
> example in
>       > > > order to understand fully.
>       > > > I was told that, given the ordinal factor, I do not need to
specify
> the
>       > > > contr.poly function because R does it automatically.
>       > > > However, I don not know if I have to add an argument into the
>       > > manova/anova
>       > > > function or something else.
>       > > > Please write me an illustrative example.
>       > > > Many thanks.
>       > > >
>       > > > Best regards,
>       > > > Gian Mauro Manzoni
>       > > >
>       > > > 2012/7/25 Greg Snow <538...@gmail.com>
>       > > >
>       > > > > You should not need to write them yourself. Look at the
> contr.poly
>       > > > > function along with the C function (Note uppercase C) or the
> contrasts
>       > > > > function.
>       > > > >
>       > > > >
>       > > > > On Monday, July 23, 2012, Manzoni, GianMauro wrote:
>       > > > >
>       > > > >> Dear all,
>       > > > >> I am quite new to R and I am having trouble writing the
> polynomial
>       > > > >> contrasts for an ordinal factor in MANOVA.
>       > > > >> # I have a model such as this
>       > > > >> fit<-manova(cbind(Y1,Y2,Y3)~Groups,data=Events) # where
> groups is an
>       > > > >> ordinal factor with 4 levels
>       > > > >> # how to set polynomial contrasts for the "Groups" factor ?
>       > > > >>
>       > > > >> Thank you very much in advance for any help!
>       > > > >>
>       > > > >> Best regards,
>       > > > >> Mauro
>       > > > >>
>       > > > >> --
>       > > > >> Dr. Gian Mauro Manzoni
>       > > > >> PhD, PsyD
>       > > > >> Psychology Research Laboratory
>       > > > >> San Giuseppe Hospital
>       > > > >> Istituto Auxologico Italiano
>       > > > >> Verbania - Italy
>       > > > >> e-mail: gm.manz...@auxologico.it
>       > > > >> cell. phone +39 338 4451207 <tel:%2B39%20338%204451207>
>       > > > >> Tel. +39 0323 514278 <tel:%2B39%200323%20514278>
>       > > > >>
>       > > > >>         [[alternative HTML version deleted]]
>       > > > >>
>       > > > >> ______________________________________________
>       > > > >> R-help@r-project.org 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.
>       > > > >>
>       > > > >
>       > > > >
>       > > > > --
>       > > > > Gregory (Greg) L. Snow Ph.D.
>       > > > > 538...@gmail.com
>       > > > >
>       > > >
>       > > >
>       > > >
>       > > > --
>       > > > Dr. Gian Mauro Manzoni
>       > > > PhD, PsyD
>       > > > Psychology Research Laboratory
>       > > > San Giuseppe Hospital
>       > > > Istituto Auxologico Italiano
>       > > > Verbania - Italy
>       > > > e-mail: gm.manz...@auxologico.it
>       > > > cell. phone +39 338 4451207 <tel:%2B39%20338%204451207>
>       > > > Tel. +39 0323 514278 <tel:%2B39%200323%20514278>
>       > > >
>       > > >       [[alternative HTML version deleted]]
>       > > >
>       > > > ______________________________________________
>       > > > R-help@r-project.org 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.
>       > >
>       > >
>       > >
>       >
>       >
>       > --
>       > Dr. Gian Mauro Manzoni
>       > PhD, PsyD
>       > Psychology Research Laboratory
>       > San Giuseppe Hospital
>       > Istituto Auxologico Italiano
>       > Verbania - Italy
>       > e-mail: gm.manz...@auxologico.it
>       > cell. phone +39 338 4451207 <tel:%2B39%20338%204451207>
>       > Tel. +39 0323 514278 <tel:%2B39%200323%20514278>
> 
> 
> 
> 
> 
> --
> Dr. Gian Mauro Manzoni
> PhD, PsyD
> Psychology Research Laboratory
> San Giuseppe Hospital
> Istituto Auxologico Italiano
> Verbania - Italy
> e-mail: gm.manz...@auxologico.it
> cell. phone +39 338 4451207
> Tel. +39 0323 514278

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