From: Birgit Lemcke <birgit.lemcke_at_systbot.uzh.ch>

Date: Sat, 17 May 2008 19:00:28 +0200

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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. Received on Sat 17 May 2008 - 18:04:06 GMT

Date: Sat, 17 May 2008 19:00:28 +0200

Thanks a lot for you explanations.

Only to complete this:

I am using glm with a quasi-poisson distribution for count data
variables and I still have problems to interpret the table that I get
back.

But that is probably more a problem of lacking statistical knowledge.

Greets

Birgit

Am 16.05.2008 um 19:10 schrieb Doran, Harold:

> Dear Berwin:

*>
**> Indeed, it seems I was incorrect. Using your data, it seems that
**> only in
**> the case that the variables are numeric would my earlier statements be
**> true, as you note. For example, if we did
**>
**> lm(y ~ as.numeric(N)+as.numeric(M), dat)
**> lm(y ~ as.numeric(N)*as.numeric(M), dat)
**> lm(y ~ as.numeric(N):as.numeric(M), dat)
**>
**> Then the latter two are different, but only under the coercion to
**> numeric.
**>
**>> -----Original Message-----
**>> From: Berwin A Turlach [mailto:berwin_at_maths.uwa.edu.au]
**>> Sent: Friday, May 16, 2008 12:27 PM
**>> To: Doran, Harold
**>> Cc: Birgit Lemcke; R Hilfe
**>> Subject: Re: [R] glm model syntax
**>>
**>> G'day Harold,
**>>
**>> On Fri, 16 May 2008 11:43:32 -0400
**>> "Doran, Harold" <HDoran_at_air.org> wrote:
**>>
**>>> N+M gives only the main effects, N:M gives only the interaction, and
**>>> G*M gives the main effects and the interaction.
**>>
**>> I guess this begs the question what you mean with "N:M gives
**>> only the interaction" ;-)
**>>
**>> Consider:
**>>
**>> R> (M <- gl(2, 1, length=12))
**>> [1] 1 2 1 2 1 2 1 2 1 2 1 2
**>> Levels: 1 2
**>> R> (N <- gl(2, 6))
**>> [1] 1 1 1 1 1 1 2 2 2 2 2 2
**>> Levels: 1 2
**>> R> dat <- data.frame(y= rnorm(12), N=N, M=M) dim(model.matrix(y~N+M,
**>> R> dat))
**>> [1] 12 3
**>> R> dim(model.matrix(y~N:M, dat))
**>> [1] 12 5
**>> R> dim(model.matrix(y~N*M, dat))
**>> [1] 12 4
**>>
**>> Why has the model matrix of y~N:M more columns than the model
**>> matrix of y~N*M if the former contains the interactions only
**>> and the latter contains main terms and interactions? Of
**>> course, if we leave the dim() command away, we will see why.
**>> Moreover, it seems that the model matrix constructed from
**>> y~N:M has a redundant column.
**>>
**>> Furthermore:
**>>
**>> R> D1 <- model.matrix(y~N*M, dat)
**>> R> D2 <- model.matrix(y~N:M, dat)
**>> R> resid(lm(D1~D2-1))
**>>
**>> Shows that the column space created by the model matrix of
**>> y~N*M is completely contained within the column space created
**>> by the model matrix of y~N:M, and it is easy to check that
**>> the reverse is also true. So it seems to me that y~N:M and
**>> y~N*M actually fit the same models. To see how to construct
**>> one design matrix from the other, try:
**>>
**>> R> lm(D1~D2-1)
**>>
**>> Thus, I guess the answer is that y~N+M fits a model with main
**>> terms only while y~N:M and y~N*M fit the same model, namely a
**>> model with main and interaction terms, these two formulations
**>> just create different design matrices which has to be taken
**>> into account if one tries to interpret the estimates.
**>>
**>> Of course, all the above assumes that N and M are actually
**>> factors, something that Birgit did not specify. If N and M
**>> (or only one of
**>> them) is a numeric vector, then the constructed matrices
**>> might be different, but this is left as an exercise. ;-)
**>> (Apparently, if N and M are both numeric, then your summary
**>> is pretty much correct.)
**>>
**>> Cheers,
**>>
**>> Berwin
**>>
**>> =========================== Full address
**>> =============================
**>> Berwin A Turlach Tel.: +65 6515 4416
**>> (secr)
**>> Dept of Statistics and Applied Probability +65 6515 6650
**>> (self)
**>> Faculty of Science FAX : +65 6872 3919
**>> National University of Singapore
**>> 6 Science Drive 2, Blk S16, Level 7 e-mail:
**>> statba_at_nus.edu.sg
**>> Singapore 117546 http://www.stat.nus.edu.sg/
**>> ~statba
**>>
*

Birgit Lemcke

Institut für Systematische Botanik

Zollikerstrasse 107

CH-8008 Zürich

Switzerland

Ph: +41 (0)44 634 8351

birgit.lemcke_at_systbot.uzh.ch

175 Jahre UZH

«staunen.erleben.begreifen. Naturwissenschaft zum Anfassen.»
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19. April 2008, 10.00 Uhr bis 02.00 Uhr

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Weitere Informationen http://www.175jahre.uzh.ch/naturwissenschaft

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