(1) Create the contrast using [-1 -1/3 1/3 1] at the single subject level. This measures the overall linear trend (it does not show 2>1, 3>2, and 4>3). At the second level, use two one-sample t-tests. The issue with the one-way repeated measure ANOVA with 2 levels (also known as the paired t-test) is that you can not test level 1 > 0 across subjects or level 2 > 0 across subjects because of the incorrect error terms (see previous emails about this). If you are using GLM Flex to do a paired t-test, then you could test level 1 and level 2 separately and see if they are different from 0.

(2) at first level, create four con image for each level of complexity in each type of stimulus (face and house) and for each subject (e.g., 10 subjects). Use a flexible factor with 3 factors (subject, condition, complexity). You can now test for interactions between condition and complexity OR test the linear contrast for complexity in the faces and then in the houses. Because you are using the within-subject comparisons, you can use this model. You have to careful though, the assumption is that SPM can correct the non-sphericity of the model. This hasn't been thoroughly tested. An alternative approach to protect against violations of sphericity is to use GLM Flex. If you stick with SPMs flexible factorial model, only within-subject comparisons are valid; the between-subject comparisons (e.g. faces > 0 or faces complexity >1, or complexity 1 > 0) are invalid because of the wrong error term and degrees of freedom.

Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.

On Wed, Feb 1, 2012 at 8:42 AM, Veda <[log in to unmask]> wrote:

Dear SPM experts,

There are two types of stimuli (face vs. house) in my experiment and each of which had four levels (linear) of visual complexity. I want to see which brain regions activate increasingly with the four levels of complexity in each of the stimuli and whether there are overlapped activations for the effect of the visual complexity of each type of stimuli. My question is how to set up second level analysis. There are two possible ways to do that
1-a. at first level, create a con image for each type of stimulus (face and house) and for each subject (e.g., 10 subjects) in which the contrast weighting of [-1 -1/3 1/3 1] are set for the four levels
1-b. at second level, submit those con images into two-way ANOVA design in which there are two con images for ten subjects

2-a. at first level, create four con image for each level of complexity in each type of stimulus (face and house) and for each subject (e.g., 10 subjects)
2-b. at second level, submit those con images into a full factorial design in which there are eight (4 level (visual complexity) x 2 type of stimuli (face vs. house)) con images for ten subject into a full factorial analysis in which factor one (face) has four levels and factor two (house) has four levels.

Could someone tell me which way is correct and why. Thanks!

Sincerely,
Veda