R help - Jan 2011 - anova vs aov commands for anova with repeated measures

Dear all,
I need to understand a thing in the beheaviour of the two functions aov and 
anova in the following case
involving an analysis of ANOVA with repeated measures:

If I use the folowing command I don´t get any problem:
>aov1 = aov(response ~ stimulus*condition +
Error(subject/(stimulus*condition)),
>data=scrd)
> summary(aov1)
Instead if I try to fit the same model for the regression I get an
error:
> fit1<- lm(response ~ stimulus*condition +
Error(subject/(stimulus*condition)),
>data=scrd) 
>
Error in eval(expr, envir, enclos) : could not find function "Error"

so I cannot run the command anova(fit1) afterwards.


I want to use fit1<- lm(response ~ stimulus*condition + 
Error(subject/(stimulus*condition)), data=scrd) 

because I want to analyze the residuals in order to check normality, and see if 
the anova assumption of normality
still holds.

Could you please help me in understanding how to do this?

Thanks in advance

Best regards


      
	[[alternative HTML version deleted]]

lm() and aov() are not fully equivalent.  They both fit linear models, but they
use different algorighms, and this allows aov, for example, to handle some
simple multistratum models.  The algorithm used by lm does not allow this, but
it has other advantages for simpler models.

If you want to fit a multistratum model, such as a repeated measures model, you
need to use aov.

When it comes to finding the residuals, you have to be explicit about which
residuals you mean, too.  You get residuals for each stratum in a multistratum
model.  Using plain old resid() will not work as that function can only be used
when there is only one kind of residuals vector defined.  (it could me made to
do something sensible, but that's another issue.  Right now, it
doesn't.)

The function proj() can be used on a fitted model object to obtain the
projections, at each stratum, on to the subspaces defined by the terms in the
model, and includes the residuals (the projection onto the orthogonal complement
of the model space in R^n) as the final column of the matrix of projections. 
These are easy to dig out and you can analyse away.

See ?proj for an example of its use, but you will need to dig out the
appropriate column yourself.

________________________________________
From: r-help-bounces at r-project.org [r-help-bounces at r-project.org] On
Behalf Of Frodo Jedi [frodo.jedi at yahoo.com]
Sent: 08 January 2011 01:51
To: r-help at r-project.org
Subject: [R] anova vs aov commands for anova with repeated measures

Dear all,
I need to understand a thing in the beheaviour of the two functions aov and
anova in the following case
involving an analysis of ANOVA with repeated measures:

If I use the folowing command I don?t get any problem:
>aov1 = aov(response ~ stimulus*condition +
Error(subject/(stimulus*condition)),
>data=scrd)
> summary(aov1)
Instead if I try to fit the same model for the regression I get an
error:
> fit1<- lm(response ~ stimulus*condition +
Error(subject/(stimulus*condition)),
>data=scrd)
>
Error in eval(expr, envir, enclos) : could not find function "Error"

so I cannot run the command anova(fit1) afterwards.


I want to use fit1<- lm(response ~ stimulus*condition +
Error(subject/(stimulus*condition)), data=scrd)

because I want to analyse the residuals in order to check normality, and see if
the anova assumption of normality
still holds.

Could you please help me in understanding how to do this?

Thanks in advance

Best regards



        [[alternative HTML version deleted]]

Bill.Venables wrote:
> 
> ...
> If you want to fit a multistratum model, such as a repeated measures
> model, you need to use aov.
> 
> 
...Or lme in nlme / lmer in lme4.

Dieter


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