From: Spencer Graves <spencer.graves_at_pdf.com>

Date: Sat 18 Jun 2005 - 06:06:00 EST

*>
*

*> # example results:
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*> Error: Snr
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*> Df Sum Sq Mean Sq F value Pr(>F)
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*> cond 1 103.1 103.1 1.425 0.248
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*> indep 5 159.8 32.0 0.442 0.813
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*> Residuals 18 1301.6 72.3
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*>
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*> Error: Snr:indep
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*> Df Sum Sq Mean Sq F value Pr(>F)
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*> indep 5 20.81 4.16 3.167 0.0104 *
*

*> Residuals 111 145.89 1.31
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*> ---
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*> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
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*>
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*> Error: Within
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*> Df Sum Sq Mean Sq F value Pr(>F)
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*> Residuals 137 22.178 0.162
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*>
*

*>
*

*>
*

*> # example results:
*

*> Error: Snr
*

*> Df Sum Sq Mean Sq F value Pr(>F)
*

*> cond 1 174.6 174.6 1.689 0.213
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*> indep 5 201.9 40.4 0.391 0.848
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*> cond:indep 5 124.0 24.8 0.240 0.939
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*> Residuals 15 1550.8 103.4
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*>
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*> Error: Snr:indep
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*> Df Sum Sq Mean Sq F value Pr(>F)
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*> indep 5 73.16 14.63 8.601 5e-07 ***
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*> cond:indep 5 21.32 4.26 2.507 0.0336 *
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*> Residuals 125 212.64 1.70
*

*> ---
*

*> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
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*>
*

*> Error: Within
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*> Df Sum Sq Mean Sq F value Pr(>F)
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*> Residuals 464 507.5 1.1
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*>
*

*>
*

*> I would like to understand a bit better what the cond:indep line under the second Error:Snr:indep can mean. If I understood correctly, this represents some "higher-order" interaction, but not a real indep/cond interaction. What I also do not grasp is why the indep effect's F and significance is so different between the two models.
*

*> Finally, what does it mean when significant effects are listed under the Error:Within line?
*

*>
*

*> Is there a good resource available (web, or if not printed) which discusses this kind of question in a way accessible to non statisticians? The last time I checked, manuals like "R for Psychologists" do not really enter into this level of detail...
*

*>
*

*> Thanks very much in advance,
*

*> R. Bertin
*

*>
*

*> ______________________________________________
*

> R-help@stat.math.ethz.ch mailing list

*> https://stat.ethz.ch/mailman/listinfo/r-help
*

*> PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
*

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Sat Jun 18 06:22:29 2005

Date: Sat 18 Jun 2005 - 06:06:00 EST

I commend you to (a) the recent article by Doug Bates on "Fitting nonlinear mixed models in R" pp. 27-30 in the latest issue of "R News" available from "www.r-project.org" -> Newsletter and (b) Doug's book with Pinheiro (2000) Mixed-Effects Models in S and S-PLUS (Springer). I suggest you try the same analysis using in "lmer", library(lme4), and "lme", library(nlme), with method = "ML", as explained in Pinheiro and Bates. If you have trouble with this, please post another question on this, preferably using either a standard data set distributed with R or one of the standard packages or a very simple made-up data set with very few observations that you can distribute with your question in a short sequence of R commands illustrating something you tried that either didn't work or that gave results you don't understand. I can't do much more with the example you've provided below, because I don't know how to access the your data. (And PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html if you haven't already.)

hope this helps. spencer graves

RenE J.V. Bertin wrote:

*> Hello,
**>
**> I'm trying to understand how to interpret the differences in results between two versions of a 2-factor ANOVA with (slightly?) different models, of an observable y, a within-subject factor 'indep' and a grouping factor 'cond' (and a subject 'factor' Snr):
**>
**>
*

>>summary( aov( y~cond + indep + Error(Snr/indep) ) )

>>summary( aov( y~cond * indep + Error(Snr/indep) ) )

> R-help@stat.math.ethz.ch mailing list

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Sat Jun 18 06:22:29 2005

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