[R] repeated measures aov with weights

[Prof Brian Ripley]

On Wed, 17 Dec 2008, Ingmar Visser wrote:

> I see, I was afraid for an answer along these lines as my problem now turns
> into a stat problem (-;Any suggestions on how to analyze such data as given
> below with weights AND at the same time
> taking into account that there are repeated measurements?

It matters what you mean by 'weights'.  If they are case weights, repeat 
the cases.  If they are inverse-variance weights, you can use package 
lme4.

List R-sig-mixed-modles might be more appropriate if you want more 
detailed help.

> 
> Best, Ingmar
> 
> On 17 Dec 2008, at 11:02, Prof Brian Ripley wrote:
>
>       Weights are not supported: multistratum aov is designed for
>       balanced designs and uses projection for which weighting is
>       inappropriate.
> 
> On Wed, 17 Dec 2008, Ingmar Visser wrote:
>
>       Dear R-help,
> 
> I'm facing a problem with defining a repeated measures anova
> with
> weighted data.
> Here's the code to reproduce the problem:
> 
> # generate some data
> seed=11
> rtrep <- data.frame(rt=rnorm(100),ti=rep(1:5,20),subj=gl
> (20,5,100),we=runif(100))
> 
> # model with within factor for subjects/repeated measurements,
> no
> problem
> aov(rt~ti + Error(subj/ti),data=rtrep)
> 
> #model with weights and subj as between factor, ie ignoring
> repeated
> measures,
> #again, no problem
> aov(rt~ti+subj,data=rtrep,weights=we)
> 
> #combination of above two: repeated measures AND weights
> aov(rt~ti + Error(subj/ti),data=rtrep,weights=we)
> 
> The latter model gives an error (see report below), but only
> after
> fitting it, ie the error is produced by the
> print and summary methods of the aov objects.
> 
> Any guidance is appreciated, best, Ingmar
> 
> 
> 
> 
> 
> Error produced in printing the fitted aov object:
> 
> Call:
> aov(formula = rt ~ ti + Error(subj/ti), data = rtrep, weights =
> we)
> Note: The results below are on the weighted scale
> 
> Grand Mean: 0.112081
> 
> Stratum 1: subj
> 
> Terms:
>                        ti Residuals
> Sum of Squares   2.002826 10.869940
> Deg. of Freedom         1        18
> 
> Residual standard error: 0.7771007
> Estimated effects are balanced
> 
> Stratum 2: subj:ti
> 
> Terms:
>                       ti Residuals
> Sum of Squares  0.382535  5.540047
> Deg. of Freedom        1        19
> 
> Residual standard error: 0.5399828
> Estimated effects are balanced
> 
> Stratum 3: Within
> Error in print.aov(xi, ...) :
>   dims [product 60] do not match the length of object [100]
> In addition: Warning message:
> In resid * wt^0.5 :
>   longer object length is not a multiple of shorter object
> length
> 
> 
> Ingmar Visser
> Department of Psychology, University of Amsterdam
> Roetersstraat 15
> 1018 WB Amsterdam
> The Netherlands
> t: +31-20-5256723
> 
> 
> 
> [[alternative HTML version deleted]]
> 
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> 
> -- 
> Brian D. Ripley,                  ripley at stats.ox.ac.uk
> Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
> University of Oxford,             Tel:  +44 1865 272861 (self)
> 1 South Parks Road,                     +44 1865 272866 (PA)
> Oxford OX1 3TG, UK                Fax:  +44 1865 272595
> 
> 
> Ingmar Visser
> Department of Psychology, University of Amsterdam
> Roetersstraat 15
> 1018 WB Amsterdam
> The Netherlands
> t: +31-20-5256723
> 
> 
> 
>

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595