MANOVA polynomial contrasts
Dear Mauro, I believe that I've answered a version of this question three times this month alone, so I'll be brief. Are you aware that if you use type-III tests, even if you are careful to employ contrasts, such as orthogonal polynomial contrasts, that are orthogonal for different terms in the row-basis of the design, you will nevertheless be testing for differences when the covariates are both 0? If that's not sensible, then why not use type-II tests? (As an aside, I've been experiencing a problem with my ISP that's causing my return email address to be given incorrectly; please don't reply to an address other than jfox at mcmaster.ca -- and, of course, r-help at r-project.org.) John
-----Original Message----- From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Manzoni, GianMauro Sent: July-30-12 5:21 PM To: jesse.fox at sympatico.ca Cc: r-help at r-project.org Subject: Re: [R] MANOVA polynomial contrasts Dear Prof. John Fox, I found the paper very useful. Thank you very much for attaching the link! Which type of SS (II or III) do you suggest for a multivariate model with
2
unbalanced factors and 2 covariates? I think that type III is the right one but .... Mauro 2012/7/30 <jesse.fox at sympatico.ca>
Dear GMM,
-----Original Message----- From: Manzoni, GianMauro [mailto:gm.manzoni at auxologico.it] Sent: July-30-12 9:49 AM To: John Fox Cc: r-help at 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 <
ix-Mul tivariate-Linear-Models.pdf>. Best, John
Best regards,
GMM
2012/7/30 John Fox <jfox at mcmaster.ca>
Dear Gian Mauro,
On Mon, 30 Jul 2012 14:44:44 +0200
"Manzoni, GianMauro" <gm.manzoni at 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 <jfox at 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.manzoni at 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 <538280 at 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.manzoni at 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 at 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.
> > > > 538280 at gmail.com
> > > >
> > >
> > >
> > >
> > > --
> > > Dr. Gian Mauro Manzoni
> > > PhD, PsyD
> > > Psychology Research Laboratory
> > > San Giuseppe Hospital
> > > Istituto Auxologico Italiano
> > > Verbania - Italy
> > > e-mail: gm.manzoni at 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 at r-project.org mailing list
> > > https://stat.ethz.ch/mailman/listinfo/r-help
> > > PLEASE do read the posting guide
> > > 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.manzoni at 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.manzoni at auxologico.it cell. phone +39 338 4451207 Tel. +39 0323 514278
-- Dr. Gian Mauro Manzoni PhD, PsyD Psychology Research Laboratory San Giuseppe Hospital Istituto Auxologico Italiano Verbania - Italy e-mail: gm.manzoni at auxologico.it cell. phone +39 338 4451207 Tel. +39 0323 514278 [[alternative HTML version deleted]]
______________________________________________ R-help at 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.