Hi Fiona,
It sounds to me like you might need a multilevel regression to analyze
these data, and if you have multiple measures (that's called a
multivariate multilevel model) it gets really hard, so you probably
want to treat them separately.
It's very similar to a regression analysis, except that you are
allowed to "stack" people, so a person becomes more than one row, and
then you have a variable that identifies which is the person. Can make
your data look like this using the 'restructure' command.
You can then have two kinds of covariates - between person covariates
are covariates that are a function of the person, and they have the
same effect on every measure; and within person covariates which can
be measured separately for each (say) task.
It's fairly fiddly though. If you're at Herts there's a guy in the
stats department whose name I've forgotten (Neil something?) who (I
think) does a bit of that sort of thing. The book that Josephine
suggested (thanks, your fiver is on the way) covers it very briefly,
but not really in enough depth to be able to do it. A good book is by
SInger and Willett (2003), although I've forgotten the title. :)
Jeremy
2009/1/22 Fiona Essig <[log in to unmask]>:
> Hi all,
>
> Hope someone can help with this as I seem to be going round in circles. I'm
> looking at Task Switching using some novel verbal based tasks. On the task
> people have to manipulate two, then three, then four verbal categories. They
> are scored on RT and accuracy. On this particular study there are two
> different types of task (basically using different types of verbal
> categories). So we are looking at what effect the number and type of
> categories being used has on Rt and accuracy.
>
> The study is repeated measures - IV1 = Test Type (A & B), IV2 = Number of
> Categories (2, 3 or 4), and I have 2 DVs of RT and accuracy.
>
> Try as I might I can't think of how to get this into one model. I've been
> reading through Tabachnik & Fidell and I'm looking at profile analysis /
> doubly-MANOVA design (and I'm a bit shaky on that!), but I can't see how to
> include the second IV of test type as well. I wonder if I may be able to
> change the way I have arranged my dataset but I really can't see what to do
> differently. Currently I have 12 main variables of interest representing the
> various combinations of the IVs and two DV measures for each person.
>
> Oh and there are a bunch of covariates thrown in for good measure as well!
>
> Previously I have used separate repeated measures ANOVAs (with adjusted
> alpha) for RT and for accuarcy but it's not really telling me what I want to
> know. As well as looking for main effects and interaction of the IVs I want
> to see how the two DVs relate to each other through these various
> combinations. I could do a profile analysis for both DVs on each test type
> separately - is this as close as I'm going to get?
>
> Many thanks in anticipation :)
>
> Fiona
>
> --
> Tel: 01707 284 761
> E-mail: [log in to unmask]
>
> Fiona Essig
> Research Student
> Room E384 Research Huts
> School of Psychology
> University of Hertfordshire
> College Lane
> Hatfield
> Herts AL10 9AB
>
--
Jeremy Miles
Psychology Research Methods Wiki: www.researchmethodsinpsychology.com
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