Ah, I see where we are talking past each other. In my particular analysis
(I'm looking at deviations from a predicted value), any deviation from 0
(whether due to grand mean or not) is actually very very interesting. What
is ultimately interesting to me is the sign of that difference, but, I nee
On 3/5/2008 3:19 PM, jebyrnes wrote:
> Indeed, but are not each of the cell means also evaluations of the effect of
> one factor at the specific level of another factor? Is this an issue of
> "Tomato, tomahto".
I don't think it is "tomato, tomahto". Say the grand mean is around
100 and the w
Indeed, but are not each of the cell means also evaluations of the effect of
one factor at the specific level of another factor? Is this an issue of
"Tomato, tomahto".
I guess my question is, if I want to know if each of those is different from
0, then should I use the 48df from the full model,
On 3/5/2008 1:32 PM, jebyrnes wrote:
> Ah. I see. So, if I want to test to see whether each simple effect is
> different from 0, I would do something like the following:
>
> cm2 <- rbind(
> "A:L" = c(1, 0, 0, 0, 0, 0),
> "A:M" = c(1, 1, 0, 0, 0, 0),
> "A:H" = c(1, 0, 1, 0, 0, 0),
> "B:L" =
Ah. I see. So, if I want to test to see whether each simple effect is
different from 0, I would do something like the following:
cm2 <- rbind(
"A:L" = c(1, 0, 0, 0, 0, 0),
"A:M" = c(1, 1, 0, 0, 0, 0),
"A:H" = c(1, 0, 1, 0, 0, 0),
"B:L" = c(1, 0, 0, 1, 0, 0),
"B:M" = c(1, 1, 0, 1, 1, 0)
On 3/5/2008 10:09 AM, jebyrnes wrote:
> Huh. Very interesting. I haven't really worked with manipulating contrast
> matrices before, save to do a prior contrasts. Could you explain the matrix
> you laid out just a bit more so that I can generalize it to my case?
Each column corresponds to
Huh. Very interesting. I haven't really worked with manipulating contrast
matrices before, save to do a prior contrasts. Could you explain the matrix
you laid out just a bit more so that I can generalize it to my case?
Chuck Cleland wrote:
>
>
>One approach would be to use glht() in t
On 3/4/2008 2:45 PM, Jarrett Byrnes wrote:
> Hello, R-i-zens. I'm working on an data set with a factorial ANOVA
> that has a significant interaction. I'm interested in seeing whether
> the simple effects are different from 0, and I'm pondering how to do
> this. So, I have
>
> my.anova<-lm
Hello, R-i-zens. I'm working on an data set with a factorial ANOVA
that has a significant interaction. I'm interested in seeing whether
the simple effects are different from 0, and I'm pondering how to do
this. So, I have
my.anova<-lm(response ~ trtA*trtB)
The output for which gives me a
9 matches
Mail list logo
