Hi Jean-Paul,
>> However, I've tried both solutions on my model, and I got different
>> residuals :...
>> What could be the difference between the two?
There is no difference. You have made a mistake.
##
tt <- data.frame(read.csv(file="tt.csv", sep="")) ## imports your data set
T.aov <- aov(PH~Community*Mowing*Water + Error(Block), data=tt)
summary(T.aov) ## This matches your output
Df Sum Sq Mean Sq F value Pr(>F)
Mowing 1 40.007 40.007 21.1747 0.0002215 ***
Water 1 23.120 23.120 12.2370 0.0025673 **
Community:Mowing 1 21.060 21.060 11.1467 0.0036554 **
Community:Water 1 6.901 6.901 3.6524 0.0720478 .
Mowing:Water 1 1.611 1.611 0.8527 0.3680090
Community:Mowing:Water 1 0.858 0.858 0.4542 0.5089331
Residuals 18 34.008 1.889
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
##
length(residuals(T.aov <- aov(PH~Community*Mowing*Water + Error(Block),
data=tt)$Within))
[1] 24
length(proj(T.aov)[,"Residuals"])
[1] 24
## Details
residuals(T.aov <- aov(PH~Community*Mowing*Water + Error(Block),
data=tt)$Within)
9 10 11 12 13
14 15 16
-1.107277057 -0.977277057 -0.007277057 -0.719777057 -1.021627882
0.215872118 -1.621627882 0.508372118
17 18 19 20 21
22 23 24
1.241311954 1.498811954 -0.616188046 0.483811954 -0.477827381
-1.660327381 2.684672619 1.924672619
25 26 27 28 29
30 31 32
-0.465198010 -1.735198010 1.502301990 0.839801990 -0.428515358
-0.751015358 0.836484642 1.181484642
proj(T.aov)[,"Residuals"]
9 10 11 12 13
14 15 16 17 18 19
20 21
-1.107277057 -0.977277057 -0.007277057 -0.719777057 -1.021627882
0.215872118 -1.621627882 0.508372118 1.241311954 1.498811954 -0.616188046
0.483811954 -0.477827381
22 23 24 25 26
27 28 29 30 31 32
-1.660327381 2.684672619 1.924672619 -0.465198010 -1.735198010
1.502301990 0.839801990 -0.428515358 -0.751015358 0.836484642 1.181484642
Regards, Mark.
Jean-Paul Maalouf wrote:
>
> Thanks Mark and Richard for your propositions on how to extract residuals.
>
> However, I've tried both solutions on my model, and I got different
> residuals :
> If we consider the within residuals :
>
> Mark's solution gave me a vector of 24 residuals :
>
>> as.vector(residuals(aov(PH~Community*Mowing*Water +
>> Error(Block))$Within))
> [1] -1.107277057 -0.977277057 -0.007277057 -0.719777057 -1.021627882
> 0.215872118 -1.621627882 0.508372118 1.241311954 1.498811954
> -0.616188046
> [12] 0.483811954 -0.477827381 -1.660327381 2.684672619 1.924672619
> -0.465198010 -1.735198010 1.502301990 0.839801990 -0.428515358
> -0.751015358
> [23] 0.836484642 1.181484642
>
> and Richard's solution gave me a vector 32 residuals :
>
> do.call(data.frame,proj(aov(PH~Community*Water*Mowing +
> Error(Block))))->proj
> proj$Within.Residuals
> [1] -0.216875 1.745625 -1.174375 -0.354375 0.800625 0.460625
> -0.799375 -0.461875 -0.404375 -0.274375 0.695625 -0.016875 -0.541875
> 0.695625 -1.141875
> [16] 0.988125 0.589375 0.846875 -1.268125 -0.168125 -1.095625
> -2.278125 2.066875 1.306875 -0.500625 -1.770625 1.466875 0.804375
> -0.638125 -0.960625
> [31] 0.626875 0.971875
>
> What could be the difference between the two?
>
> Regards
>
> JPM
>
>
> Quoting "Richard M. Heiberger" <r...@temple.edu>:
>
>> Jean-Paul Maalouf wrote:
>>> Do you have any idea on how can I verify preliminary assumptions in
>>> this model (normality of the residuals and variance homogeneity),
>>> since R is not able to extract residuals?
>>
>> Of course, R extracts residuals. Use the proj() function. See ?proj
>> for the example
>> to get the projection of an aovlist object onto the terms of a linear
>> model
>>
>> proj(npk.aovE)
>>
>>
>> To get the projections into a simple data.frame, use
>> tmpE <- proj(npk.aovE)
>> tmpE.df <- do.call("data.frame", tmpE)
>> tmpE.df
>>
>> Mark Difford's solution effectively retrieved columns 3 and 10 from
>> tmpE.df
>>
>> Rich
>
>
>
> --
> Jean-Paul Maalouf
> UMR 1202 BIOGECO
> Inra - Université Bordeaux 1
> Bâtiment B8, Avenue des Facultés
> 33405 Talence, France
> Tel : 05 40008772
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>
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