Hi,
Yes I had suspected I might be looking at something horribly involved :(
Regarding the previous reply suggesting adding several DVs into the
GLM-repeated measures option in SPSS - what would be the reasons for not
doing it that way? I have just quickly run that and it's given me a
stupendous amount of output (which might be one reason!), but will this
this give me increased error or something similar?
Fiona
On Jan 22 2009, Jeremy Miles wrote:
>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
>>
>
>
>
>
--
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
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