Dear Payal,
With within-subject factors only, you could indeed use the "pooled
error" approach, implemented with a flexible factorial design with three
factors: subject, age and song, and test for main effects of age, main
effect of song and age x song interaction, with F-contrasts given by:
spm_make_contrasts([3 3])
Alternatively you can use a "partitioned error" approach as described
here and in Martyn McFarquhar's paper cited within:
https://en.wikibooks.org/wiki/SPM/Group_Analysis
Best regards,
Guillaume.
On 21/06/2019 18:16, Payal Arya wrote:
> Hi Spm users
>
> after going through the archives related to flexible factorial design
> for within subject factors. I have few questions , i was hoping i could
> get answers for them.
>
> I have two factors which are within subject- *age* of the birds (cute
> little songbirds) at which they are scanned and *song* type played
> during scanning. Songs have three levels and age has three levels.
>
> So I only have one group of 16 birds which are scanned at different age
> while listening to different songs.
>
> I made single subject design at 1st level at every age when they were
> scanned.
> question 1:
>
> Now can i set up a flexible factorial design with age as one within
> factor and song as second within factor and use contrasts from ist
> level- song1>song2 or song2>song1?
>
> question 2:
>
> will the results of main effect of stimulus and main effect of age be
> valid ?
>
> questions3:
>
> also is the interaction between two factors valid in such a case?
>
> Thank you for your help
>
> Payal
>
>
--
Guillaume Flandin, PhD
Wellcome Centre for Human Neuroimaging
UCL Queen Square Institute of Neurology
London WC1N 3BG
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