Dear Andrew,
Could you please comment further on how to enter images in the second level analysis ? We are here in trouble since your message to Stephen (At 10:45 28/10/99 +0100), where you said :
>It's contrast images from a first level (individual subject say) analysis that can be re-entered into SPM to effect an analysis at a higher level (across subjects say). In SPM99 these are names con_????.img.
>.....................
>Contrast images are used because they are guaranteed to be estimable whatever the design. In general the parameter images (beta_????.img) are not estimable: The "parameter estimability" bar on SPM printouts tells you which parameters are uniquely estimable for this model. A contrast with a single "1" picking out these estimable parameters would be a valid contrast, and the contrast image would be the same as the parameter image.
When I ran a RFX analysis in SPM96, according to the helpfile, I create adjusted mean images for each subject and each condition, using for example "MultiSubj: Condition means (AnCova by subject)", assuming that (in spm_adjmean_ui.m) "Once the weights have been worked out for each adjusted mean image, computation proceeds by passing appropriate weights and image filenames to spm_mean, which writes out the appropriate parameter image .... as the input images.". Then, I entered these adjusted images in the second level analysis, compare par pairs only, and so on ...
In SPM99, it seems that two possibilities exist : either use the "AdjMean" option in the same way as in SPM96, or use in the statistics section the PET model : "Multi-subjects : condition by subject interactions and covariates", given that in both cases I ensure subject-separability using the within group options for centering, scaling and Ancova.
So, the point here is that I obtain adjusted images for subj1Xcond1, subj1Xcond2, etc .... in the first case, and with the second method I obtain corresponding beta_????.img but *not* con_????.img. Until now I was thinking that to enter those beta_????.img in the 2nd level of the analysis was the right way, because I believed that these are equivalent to the adjusted images obtained with the fisrt method.
However, you say here that beta_????.img are not uniquely estimable, hence I check my two designs and discover that in both cases (statistics or adjmean) these are indeed not. Now the problem is that I cannot really figure out how to handle con_????.img . I cannot create one for for each subject in each condition, because these are the product of the comparison between two conditions, and if it is the case, how to compare comparisons ? I'm sure I missed a point here, but I cannot see where.
Many thanks for your help,
Philippe
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PEIGNEUX Philippe, Lic. Psych., Chercheur
E-mail: [log in to unmask]
Cyclotron Research Centre
Neurology Unit & Neuropsychology Department
Liege University BELGIUM
http://www.ulg.ac.be/neuropsy/
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