Ok, I see. Thanks a lot!
Steve Smith wrote:
> Hi - no, I think that if the levels are categorical levels that
> represent the full set of levels that you are interested in, then you
> consider the ANOVA to be "fixed".
> Cheers.
>
>
> On 15 Jan 2009, at 12:58, Hanne Lehn wrote:
>
>> Hi again,
>>
>> You are right that the results look more meanigful if I treat the
>> factors as fixed effects. However, I assumed that my factors (A and
>> B) were random effects, because all four levels (A1, A2, B1, B2) were
>> measured in each subject. Is that not correct?
>>
>> Regards,
>> Hanne
>>
>> Steve Smith wrote:
>>> This depends - it is more likely that your factors are "fixed effect
>>> factors" (which is a completely separate issue to the choice of
>>> mixed effects cross-subject variance modelling that you correctly
>>> chose in the FEAT GUI). If this is the case then you don't need to
>>> take those ratios - the 3 F stats and derived Zfstat images that
>>> FEAT gives you are already what you want. Maybe this will then give
>>> you results which you find more meaningful.
>>>
>>> Cheers.
>>>
>>>
>>>
>>> On 14 Jan 2009, at 13:16, Hanne Lehn wrote:
>>>
>>>> Hi,
>>>>
>>>> I have a question about ANOVA analysis in FEAT.
>>>>
>>>> I have just run a 2x2 ANOVA on my data (two factors, both repeated
>>>> measures and with two levels). The inputs were 76 cope files (19
>>>> subjects x 4
>>>> levels), derived from the first and second level GLM (within
>>>> subjects). I
>>>> specified the design matrix as suggested in the 2x2 example on the
>>>> website,
>>>> but replaced EV4 with 19 subject-specific EVs. This gave me a total
>>>> 22 EVs. I
>>>> chose mixed effects modelling and requested three F-tests, for the
>>>> two main
>>>> effects and the interaction effect. As suggested in the web
>>>> example, I divided
>>>> the output fstat images of the two main effects by the fstat image
>>>> of the
>>>> interaction effect, and then converted these to zfstat images.
>>>>
>>>> Is this the correct way to do it?
>>>>
>>>> The reason I ask is that the results are quite different from what
>>>> I expected,
>>>> based on the standard GLM analysis (pairwise comparisons). For
>>>> example, the
>>>> standard analysis shows a large difference between the two levels
>>>> of factor A
>>>> (A1>A2), but the ANOVA shows no main effect of factor A. The two
>>>> zfstat
>>>> images look a bit odd, they contain scatters of single voxels, and
>>>> clusters
>>>> appear only with z 0-1.5. The original zfstat images look more
>>>> "normal", and in
>>>> line with my predictions, as does the zfstat image of the
>>>> interaction effect.
>>>>
>>>> If anyone knows whether and where I went wrong, please let me know.
>>>> Thanks in advance!
>>>>
>>>> Hanne
>>>>
>>>
>>>
>>> ---------------------------------------------------------------------------
>>>
>>> Stephen M. Smith, Professor of Biomedical Engineering
>>> Associate Director, Oxford University FMRIB Centre
>>>
>>> FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK
>>> +44 (0) 1865 222726 (fax 222717)
>>> [log in to unmask] http://www.fmrib.ox.ac.uk/~steve
>>> ---------------------------------------------------------------------------
>>>
>>
>> --
>> Hanne Lehn
>> PhD student Neuroscience
>>
>> MR-Centre, St. Olav's Hospital
>> 7006 Trondheim, Norway
>> Phone: (+47) 73 59 88 04
>> Fax: (+47) 73 86 77 08
>>
>
>
> ---------------------------------------------------------------------------
>
> Stephen M. Smith, Professor of Biomedical Engineering
> Associate Director, Oxford University FMRIB Centre
>
> FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK
> +44 (0) 1865 222726 (fax 222717)
> [log in to unmask] http://www.fmrib.ox.ac.uk/~steve
> ---------------------------------------------------------------------------
>
--
Hanne Lehn
PhD student Neuroscience
MR-Centre, St. Olav's Hospital
7006 Trondheim, Norway
Phone: (+47) 73 59 88 04
Fax: (+47) 73 86 77 08
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