Thanks for nice explanation.
Unfortunately, matrix in my question is exactly similar to the one I posted
earlier :
mat <- matrix(rnorm(700), ncol=5, dimnames=list( paste("f", c(1:140),sep="_"),
c("A", "B", "C", "D", "E")))
Question here is which of the 140 characteristics (i.e. f_1...f_140)
distinguish the most between the five plant
species.
Is it true that this matrix can't be regressed with factor responses (species)
? If so, what alternatives can be used ?
- Vickie
----------------------------------------
> From: j...@mcmaster.ca
> To: is...@live.com
> CC: r-help@r-project.org
> Subject: RE: [R] dropterm in MANOVA for MLM objects
> Date: Wed, 8 Feb 2012 20:37:37 -0500
>
> Dear Vickie,
>
> I'm afraid that the test problem that you've constructed makes no sense, and
> doesn't correspond to the problem that you initially described, in which a
> matrix of presumably 5 responses for presumably 140 observations is
> regressed on 6 predictors. You regressed your randomly generated matrix of 5
> responses and 140 observations on a factor constructed from the distinct 140
> observation names. That factor has 140 levels, and so the model uses 140 df,
> all the df in the data. It's therefore not surprising that the error SSP
> matrix has 0 df, which is exactly what Anova.mlm (actually,
> linearHypothesis.mlm, which it calls) tells you.
>
> The remark that you found about univariate tests that you apparently found
> on-line concerns repeated-measures designs and is not relevant to your data.
> And you can't do a univariate ANOVA when there's 0 df for error in any
> event.
>
> Here's a proper simulation of the kind of data that I think you have:
>
> > set.seed(12345)
> > E <- matrix(rnorm(140*5), ncol=5)
> > X <- matrix(rnorm(140*6), ncol=6)
> > Beta <- matrix(runif(6*5), ncol=5)
> > Y <- X %*% Beta + E
> > colnames(Y) <- c("A", "B", "C", "D", "E")
> > colnames(X) <- c("syct", "mmin", "mmax", "cach", "chmin", "chmax")
> > Data <- as.data.frame(cbind(Y, X))
> > mod <- lm(cbind(A, B, C, D, E) ~ syct + mmin + mmax + cach + chmin +
> chmax, data=Data)
> > Anova(mod)
>
> Type II MANOVA Tests: Pillai test statistic
> Df test stat approx F num Df den Df Pr(>F)
> syct 1 0.41622 18.395 5 129 9.31e-14 ***
> mmin 1 0.48288 24.091 5 129 < 2.2e-16 ***
> mmax 1 0.62100 42.273 5 129 < 2.2e-16 ***
> cach 1 0.61711 41.583 5 129 < 2.2e-16 ***
> chmin 1 0.72547 68.180 5 129 < 2.2e-16 ***
> chmax 1 0.54825 31.311 5 129 < 2.2e-16 ***
> ---
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> Best,
> John
>
> > -----Original Message-----
> > From: Vickie S [mailto:is...@live.com]
> > Sent: February-08-12 5:53 PM
> > To: j...@mcmaster.ca
> > Cc: r-help@r-project.org
> > Subject: RE: [R] dropterm in MANOVA for MLM objects
> >
> >
> > Dear Prof Fox,
> > I tried anova but got the following error message:
> >
> > mat <- matrix(rnorm(700), ncol=5, dimnames=list( paste("f", c(1:140),
> > sep="_"), c("A", "B", "C", "D", "E"))) summary(Anova(lm(cbind(A, B, C,
> > D, E) ~ factor(rownames(mat)), data=as.data.frame(mat))))
> >
> > Error in summary(Anova(lm(cbind(A, B, C, D, E) ~
> > factor(rownames(mat)), :
> > error in evaluating the argument 'object' in selecting a method for
> > function 'summary': Error in linearHypothesis.mlm(mod, hyp.matrix.2,
> > SSPE = SSPE, V = V, ...) :
> > The error SSP matrix is apparently of deficient rank = 0 < 5
> >
> > I looked in previous forum and it seems like i have only option of
> > performing the univariate test here.
> >
> > Therefore I used the following, but it still results in an error
> > message:
> > Anova(lm(cbind(A, B, C, D, E) ~ factor(rownames(mat)),
> > data=as.data.frame(mat)), univariate=TRUE, multivariate=F) Error in
> > linearHypothesis.mlm(mod, hyp.matrix.2, SSPE = SSPE, V = V, ...) :
> > The error SSP matrix is apparently of deficient rank = 0 < 5
> >
> > Any suggestions ?
> >
> > Thanks
> > Vickie
> >
> >
> >
> > I think I am still missing some important clues here. Is it because
> > the feww
> >
> > > From: j...@mcmaster.ca
> > > To: is...@live.com
> > > CC: r-help@r-project.org
> > > Subject: RE: [R] dropterm in MANOVA for MLM objects
> > > Date: Wed, 8 Feb 2012 17:01:34 -0500
> > >
> > > Dear Vicki,
> > >
> > > I think that the Anova() function in the car package will do what
> > you
> > > want (and will also properly handle models with more structure, such
> > > as interactions).
> > >
> > > Best,
> > > John
> > >
> > > --------------------------------
> > > John Fox
> > > Senator William McMaster
> > > Professor of Social Statistics
> > > Department of Sociology
> > > McMaster University
> > > Hamilton, Ontario, Canada
> > > http://socserv.mcmaster.ca/jfox
> > >
> > >
> > >
> > >
> > > > -----Original Message-----
> > > > From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
> > > > project.org] On Behalf Of Vickie S
> > > > Sent: February-08-12 3:57 PM
> > > > To: r-help@r-project.org
> > > > Subject: [R] dropterm in MANOVA for MLM objects
> > > >
> > > >
> > > > Dear R fans,
> > > > I have got a difficult sounding problem.
> > > >
> > > > For fitting a linear model using continuous response and then for
> > > > re- fitting the model after excluding every single variable, the
> > > > following functions can be used.
> > > > library(MASS)
> > > > model = lm(perf ~ syct + mmin + mmax + cach + chmin + chmax, data
> > =
> > > > cpus) dropterm(model, test = "F")
> > > >
> > > > But I am not sure whether any similar functions is available in R
> > > > for multivariate data with categorical response.
> > > > My data looks like the following:
> > > > mat <- matrix(rnorm(700), ncol=5, dimnames=list( paste("f",
> > > > c(1:140), sep="_"), c("A", "B", "C", "D", "E")))
> > > >
> > > > There are 140 features describing 5 different plant species. I
> > want
> > > > to retain only those features that show good performance in model
> > > > (by using a function similar to dropterm, which can not be used
> > for
> > > > mlm objects).
> > > >
> > > > I wud appreciate some hints n suggestions.
> > > >
> > > > Thx
> > > > - Vickie
> > > >
> > > >
> > > >
> > > >
> > > >
> > > > [[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.
> > >
> > =
>
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