(in my data that started this thread,
all the variables were within-subjects). So you may want to check about
that as well.
Best of luck,
Steve
Message: 73
Date: Tue, 11 Sep 2012 00:22:21 -0700 (PDT)
From: semperparatus
To: r-help@r-project.org
Subject: Re: [R] Contrasts for 2x4 interacti
Thanks for your response. First time posting on any R forum, and apparently
I didn't read carefully enough to see the difference in my model. I much
appreciate the quick response.
On Tue, Sep 11, 2012 at 2:16 AM, David Winsemius [via R] <
ml-node+s789695n4642723...@n4.nabble.com> wrote:
>
> On Se
On Sep 10, 2012, at 5:59 PM, semperparatus wrote:
> I want to change it because I don't want to compare in this instance between
> conditions, but I simply want to see the contrast t-statistic between
> patient and control at every level of condition (1, 2, and 3).
>
>> From there I'd like to be
I want to change it because I don't want to compare in this instance between
conditions, but I simply want to see the contrast t-statistic between
patient and control at every level of condition (1, 2, and 3).
>From there I'd like to be able to plot the t-statistic for the contrast
between patient
On Sep 10, 2012, at 5:14 PM, semperparatus wrote:
> Your problem seems to be exactly the problem I've been having for the past
> week. So glad to find this thread.
> However, when I follow the syntax you used to get around the issue, I still
> didn't get the output to work in the way yours did.
Your problem seems to be exactly the problem I've been having for the past
week. So glad to find this thread.
However, when I follow the syntax you used to get around the issue, I still
didn't get the output to work in the way yours did. I don't believe my
factors are truly nested however (nor yo
Rich,
Thank you very much for your response and the example! I think this solved
my problem completely. I am using lmer rather than aov for my model, though
(I have crossed random effects for subjects and items), so I'd just like to
check and make sure I'm understanding the model output correctly,
Stephen,
You are looking for the nesting of the FirstFactor within the SecondFactor.
Here is an example for your two-way design.
The model.matrix shows the dummy variables.
The last four columns show the two-level comparisons of Fir within each
level of Sec
Rich
tmp <- data.frame(y=rnorm(16),
Hello everyone,
I am running a mixed effects model where I have two fixed factors, one with
2 levels and one with 4, and their interaction. Let's say these are my
factors and their levels:
FirstFactor: 1, 2
SecondFactor: A, B, C, D
For the interaction, I am interested in the four two-way compari
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