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: jfox at mcmaster.ca
To: isvik at live.com
CC: r-help at 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-bounces at r-project.org [mailto:r-help-bounces at r-
project.org] On Behalf Of Vickie S
Sent: February-08-12 3:57 PM
To: r-help at 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
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