R help - Sep 2008 - aov or lme effect size calculation

(A repost of this request with a bit more detail)

Hi, All.  I'd like to calculate effect sizes for aov or lme and seem  
to have a bit of a problem.  partial-eta squared would be my first  
choice, but I'm open to suggestions.

I have a completely within design with 2 conditions (condition and  
palette).

Here is the aov version:

 > fit.aov <- (aov(correct ~ cond * palette + Error(subject),  
data=data))
 > summary(fit.aov)

Error: subject
          Df  Sum Sq Mean Sq F value Pr(>F)
Residuals 15 0.17326 0.01155

Error: Within
             Df  Sum Sq Mean Sq F value    Pr(>F)
cond          1 0.32890 0.32890  52.047 4.906e-09 ***
palette       1 0.21971 0.21971  34.768 4.447e-07 ***
cond:palette  1 0.50387 0.50387  79.735 1.594e-11 ***
Residuals    45 0.28437 0.00632
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05
'.' 0.1 ' ' 1

and here is the lme version:

 > fm1 <- lme(correct ~ cond * palette, random=~1 | subject, data=data)
 > anova(fm1)
             numDF denDF  F-value p-value
(Intercept)      1    45 4031.042  <.0001
cond             1    45   52.047  <.0001
palette          1    45   34.768  <.0001
cond:palette     1    45   79.735  <.0001

Thanks so much!
Greg

Greg

You haven't really explained what your problem is. If it is conceptual
(i.e., how do I do it) this is not really the right place for in-depth
statistical advice, but it is often given. OTOH, if your problem is
computational, please explain what that is? For example, maybe you know
how to compute eta-squared, but you want to extract the variance
component and you can't figure that out.

Without more info, it is hard to help. Now, with that said, with lme (or
mixed models) you have multiple variance components, so how would you go
about computing eta-squared anyhow?
> -----Original Message-----
> From: r-help-bounces at r-project.org 
> [mailto:r-help-bounces at r-project.org] On Behalf Of Greg Trafton
> Sent: Tuesday, September 02, 2008 10:25 AM
> To: r-help at r-project.org
> Subject: [R] aov or lme effect size calculation
> 
> (A repost of this request with a bit more detail)
> 
> Hi, All.  I'd like to calculate effect sizes for aov or lme 
> and seem to have a bit of a problem.  partial-eta squared 
> would be my first choice, but I'm open to suggestions.
> 
> I have a completely within design with 2 conditions 
> (condition and palette).
> 
> Here is the aov version:
> 
>  > fit.aov <- (aov(correct ~ cond * palette + Error(subject),
> data=data))
>  > summary(fit.aov)
> 
> Error: subject
>           Df  Sum Sq Mean Sq F value Pr(>F) Residuals 15 
> 0.17326 0.01155
> 
> Error: Within
>              Df  Sum Sq Mean Sq F value    Pr(>F)
> cond          1 0.32890 0.32890  52.047 4.906e-09 ***
> palette       1 0.21971 0.21971  34.768 4.447e-07 ***
> cond:palette  1 0.50387 0.50387  79.735 1.594e-11 ***
> Residuals    45 0.28437 0.00632
> ---
> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05
'.' 0.1 ' ' 1
> 
> and here is the lme version:
> 
>  > fm1 <- lme(correct ~ cond * palette, random=~1 | subject, 
> data=data)  > anova(fm1)
>              numDF denDF  F-value p-value
> (Intercept)      1    45 4031.042  <.0001
> cond             1    45   52.047  <.0001
> palette          1    45   34.768  <.0001
> cond:palette     1    45   79.735  <.0001
> 
> Thanks so much!
> Greg
> 
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