This analysis method is effective but antiquated.
The method of using lags with binary stim_files (and especially
-stim_nptr) has been replaced with use of TENT functions. For
details, please see the handout for the "Deconvolution" bootcamp class:
AFNI class: Deconvolution
For an example of the current processing style, consider reviewing
the handout for the "Soup to Nuts" bootcamp class:
AFNI class: Start To Finish
HowTo 05 : Group Analysis - AFNI 3dANOVA2
background : |
experiment |
- overview of the experiment, data and analysis |
|
ANOVA |
- overview of Analysis of Variance |
|
Linux scripts : |
@analyze_ht05 |
- script for individual subject analysis |
|
@anova_ht05 |
- script for group analysis |
|
main help pages: |
AFNI_howto_subject |
- explanation of the shell script: subject analysis |
|
AFNI_howto_group |
- explanation of the shell script: group analysis |
|
|
|
download : |
ht05_html.tgz |
- download script and html pages |
|
ht05_full.tgz |
- download everything (includes data : 500 Megabytes!) |
This HowTo is based on the paper:
Beauchamp, M.S., Lee, K.E., Haxby, J.V., & Martin, A. (2003).
FMRI responses to video and point-light displays of moving
humans and manipulable objects.
Journal of Cognitive Neuroscience, 15:7, 991-1001.