Hello Thijs,

I think that as you wrote, the aov wouldn't work for you here (due to the
unbalanced design).
I'd recommend you to have a look at the
{ez<http://cran.r-project.org/web/packages/ez/index.html>
} package, which offers a nice wrapping of the car Anova functions.
I've listed a bunch of tutorials on the topic here:
http://www.r-statistics.com/2010/04/repeated-measures-anova-with-r-tutorials/
That might prove useful for you.

Best,
Tal

<http://www.r-statistics.com/2010/04/repeated-measures-anova-with-r-tutorials/>

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On Sun, Oct 17, 2010 at 10:03 PM, Thijs Muizelaar <thijs.muizelaar@xs4all.nl
> wrote:

> Dear R-list members,
>
> I've been struggling with the proper setup for analysing my data. I've
> performed a route choice experiment, in which participants had to make a
> choice at each junction for the next road. During the experiment they
> received traffic information, but also encountered two different accidents.
> They also made trips without accidents.
>
> What I'm interested in is to see if the traffic information influenced
> their route choice, regarding their total travel time, the delay and the
> number of junctions they passed. These are thus three dependent variables.
>
> The independent variables are the type of traffic information and the
> accident situation, and personal characteristics such as age, gender and
> amount of kilometers driven each year. In order to simplify this, I've
> seperated each accident in a data frame (because the trips without
> accidents, don't have all the different types of traffic information).
>
> As far as my limited statical knowledge goes, this implies I have a mixed
> repeated measurements experiment. To be able to answer the hypotheses that
> traffic information influences traveltime, delay and number of junctions, I
> can do an Anova. However, the datasets are also unbalanced, because not all
> trips lead to the right destination.
>
> I've found that the car package presents the proper tools to do this, but
> I'm not sure if the following model will give the results I want to have.
> Can anyone help me with that?
>
> I've put the data in a wide format, where traveltime.1 stands for the
> measured traveltime with traffic information 1, etc.
>
> event1.mod.car<-lm(cbind("traveltime.1","traveltime.2","traveltime.3")~age*gender*kmyear,
> data=event1.wide)
> event1.aov.car<-Anova(event1.mod.car, idata=idata, idesign=~guidanceID)
>
> Can I also use the aov function? But because of the unbalanced data, this
> will probably not provide the right results. Is that right?
>
> event1.aov<-aov(traveltime~guidanceID*gender*age*kmyear +
> Error(userID/guidanceID), data=event1)
>
> Thanks in advance!
>
>
> Thijs Muizelaar
> PhD student University of Twente
>
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> PLEASE do read the posting guide
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> and provide commented, minimal, self-contained, reproducible code.
>

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