On Jan 6, 2007, at 8:34 AM, John Cardinale wrote:
Are there any R function which can do analysis of covariance?
?lm
RSiteSearch('ancova')
_
Professor Michael Kubovy
University of Virginia
Department of Psychology
USPS: P.O.Box 400400Charlottesville, VA
On 1/6/07, Michael Kubovy [EMAIL PROTECTED] wrote:
On Jan 6, 2007, at 8:34 AM, John Cardinale wrote:
Are there any R function which can do analysis of covariance?
?lm
RSiteSearch('ancova')
Given the question, you'll probably need to find how to do an ancova
with lm. Several documents in
Please look at the help file
?ancova
in the HH package.
Please get HH_1.17 which was up on CRAN yesterday. The source
file has propagated to the mirrors. As of a few minutes ago,
the Windows binary is on cran.at.r-project.org but not yet at the mirrors.
Be sure to have history recording on in
To get the ANCOVA table you need to look at the anova() function.
The variables T and L must be factors to get the multi-degree-of-freedom
anova tables you are looking for.
Order matters. You get the same residual, but the sequential sums of
squares differ.
bt.aov - aov(E ~ B + T)
[EMAIL PROTECTED] writes:
I'm trying to perform ANCOVAs in R 1.14, on a Mac OS X, but I can't figure out
?! There's no version 1.14 of R.
what I am doing wrong. Essentially, I'm testing whether a number of
quantitative dental measurements (the response variables in each ANCOVA) show
sexual
On Sat, 2006-05-20 at 08:36 +0200, Peter Dalgaard wrote:
[EMAIL PROTECTED] writes:
I'm trying to perform ANCOVAs in R 1.14, on a Mac OS X, but I can't figure
out
?! There's no version 1.14 of R.
Looking at the Mac page on CRAN, I suspect that this is the GUI version
number, rather than
I don't understand: I just ran the first example in the aov help
page, and it produced F ratios and p values.
If this does not answer your question, I suggest you read Pinheiro
and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer) if you
haven't already and try
What search terms did you use? Have you considered the multcomp
and multtest packages?
spencer graves
p.s. If you'd like more help from this list, I suggest you read the
posting guide! www.R-project.org/posting-guide.html. Anecdotal
evidence suggests that posts more closely
Mon cher M. MENICACCI:
It looks to me like you ultimately want to use lmer in
library(lme4) [which also requires library(Matrix)]. For documentation,
I suggest you start with Doug Bates (2005) Fitting Linear Mixed Models
in R, R News, vol. 5/1: 27-30 (available from
Dear Matt,
The sequential sums of squares produced by anova() test for g ignoring x
(and the interaction), x after g (and ignoring the interaction), and the x:g
interaction after g and x. The second and third test are generally sensible,
but the first doesn't adjust for x, which is probably not
This sounds like a good case for mixture regression, for which there's Fritz
Leisch's `flexmix' package. However, I don't think flexmix has facility for
testing whether the mixture has one vs. two components. Others on the list
surely would know more than I do.
HTH,
Andy
From: Rob Knell
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