On Mon, Nov 21, 2011 at 1:28 PM, Giovanni Azua brave...@gmail.com wrote:
On Nov 21, 2011, at 8:31 PM, Bert Gunter wrote:
we disagree is that I think data analysts with limited statistical
backgrounds should consult with local statisticians instead of trying
to muddle through on their own thru
On Nov 22, 2011, at 10:35 AM, Joshua Wiley wrote:
It is true the way you use general lists is not our business, but the
R-help list is a community and there are community rules. One of
I meant that my use of the lists is not of __his__ business I wasn't referring
to you nor other people in
On Tue, Nov 22, 2011 at 2:09 PM, Giovanni Azua brave...@gmail.com wrote:
Mr. Gunter did not read/understand my problem, and there were no useful tips
but only ad hominem attacks. By your side-taking I suspect you are in the
same party club if you want to defend him maybe you should start by
On Nov 22, 2011, at 3:52 PM, Liviu Andronic wrote:
On Tue, Nov 22, 2011 at 2:09 PM, Giovanni Azua brave...@gmail.com wrote:
Mr. Gunter did not read/understand my problem, and there were no useful tips
but only ad hominem attacks. By your side-taking I suspect you are in the
same party club
Hello,
I know there is plenty of people in this group who can give me a good answer :)
I have a 2^k model where k=4 like this:
Model 1) R~A*B*C*D
If I use the * in R among all elements it means to me to explore all
interactions and include them in the model i.e. I think this would be the so
Hello,
Couple of clarifications:
- A,B,C,D are factors and I am also interested in possible interactions but the
model that comes out from aov R~A*B*C*D violates the model assumptions
- My 2^k is unbalanced i.e. missing data and an additional level I also include
in one of the factors i.e. C
-
Giovanni:
1. Please read ?formula and/or An Introduction to R for how to specify
linear models in R.
2. Correct specification of what you want (if I understand correctly) is
log(R) ~ A*B + C + D
3. ... which presumably will also fail because some of your factors
have only one level, which means
Hello Bert,
Thank you for taking the time to try to answer.
1) I know this, however if one is interested in only interaction between two
specific factors then in R one uses I(A*B*C) meaning 3-way anova for that and
not the implicit 2-ways that would otherwise be computed.
2) True, but it
Onderwerp: Re: [R] [OT] 1 vs 2-way anova technical question
Hello Bert,
Thank you for taking the time to try to answer.
1) I know this, however if one is interested in only interaction between two
specific factors then in R one uses I(A*B*C) meaning 3-way anova for that and
not the implicit 2
luck.
Rob
-Original Message-
From: Giovanni Azua
Sent: Monday, November 21, 2011 4:59 PM
To: r-help@r-project.org
Subject: Re: [R] [OT] 1 vs 2-way anova technical question
Hello Bert,
Thank you for taking the time to try to answer.
1) I know this, however if one is interested in only
-help-boun...@r-project.org]
Namens Giovanni Azua
Verzonden: maandag 21 november 2011 17:00
Aan: r-help@r-project.org
Onderwerp: Re: [R] [OT] 1 vs 2-way anova technical question
Hello Bert,
Thank you for taking the time to try to answer.
1) I know this, however if one is interested in only
Hello Rob,
Thank you for your suggestions. I tried glm too without success. Anyhow I
include all the information just in case someone with good knowledge can give
me a hand with this. I take log of the response variable because:
- its values span across multiple orders of magnitudes
- the
On Nov 21, 2011, at 8:31 PM, Bert Gunter wrote:
we disagree is that I think data analysts with limited statistical
backgrounds should consult with local statisticians instead of trying
to muddle through on their own thru lists like this. This is not meant
I think that people lacking reading
This sort of post seems to me to be completely unacceptable.
Is there a mechanism by which the list manager can unsubscribe
Mr. Azua and keep him unsubscribed until he learns some manners?
cheers,
Rolf Turner
On 22/11/11 10:28, Giovanni Azua wrote:
On Nov 21, 2011, at 8:31 PM,
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