Tutorial stats 011422: Difference between revisions
Jump to navigation
Jump to search
Content added Content deleted
(Created page with "!!UNDER CONSTRUCTION!!") |
|||
| (7 intermediate revisions by 2 users not shown) | |||
| Line 1: | Line 1: | ||
!!UNDER CONSTRUCTION!! |
=!!UNDER CONSTRUCTION!!= |
||
== Tutorial Session == |
|||
Recording Download: [https://megcore.nih.gov/MEG/ClubMEG_Carver&Stout_MNE&AFNI-GroupAnalysisTutorial_012122.mp4 MNE & AFNI Group Analysis Tutorial (mp4)] |
|||
== Afni Prep == |
|||
=== Install Afni on computer: === |
|||
https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/background_install/install_instructs/index.html |
|||
=== Statistical Processing in AFNI === |
|||
#! /bin/bash |
|||
# First things first: Good practice to convert .nii files to afni .HEAD .BRIK format: 3dcopy mydataset.nii myafnidataset |
|||
# Here the data have been converted to common space (+tlrc) but if not can be done in afni with adwarp |
|||
# Example: One Sample T-test on alpha band log ratio of face power and shape power |
|||
# Why log-ratio? log(faces/shapes) = log(faces) - log(shapes) ; log attentuates outliers , normalizes distribution. |
|||
# First make a list of subjects for test: |
|||
ls *_7_13_*lograt*.HEAD > alpha_list |
|||
# Then run one sample T-test |
|||
3dttest++ -setA `cat alpha_list` -prefix alpha_ttest |
|||
# Optional: add effect size to output |
|||
3dMean -prefix alpha_mean `cat alpha_list` |
|||
3dMean -sd -prefix alpha_std `cat alpha_list` |
|||
3dcalc -prefix alpha_effectsize -a alpha_mean+tlrc -b alpha_std+tlrc -expr 'a/b' |
|||
3dbucket -prefix alpha_ttest_effectsize alpha_ttest+tlrc alpha_effectsize+tlrc |
|||
3drefit -sublabel 2 "effectsize" alpha_ttest_effectsize+tlrc |
|||
# Could do a paired T-test between faces and shapes instead of log-ratio |
|||
ls *_7_13_*shape*.HEAD > alpha_shape_list |
|||
ls *_7_13_*face*.HEAD > alpha_face_list |
|||
3dttest++ -setA `cat alpha_face_list` -setB `cat alpha_shape_list` -paired -prefix alpha_paired_ttest |
|||
# Can add covariates to T-tests. |
|||
# Can do mixed-effects ANOVAs and other fancier stuff |
|||
== MNE Python == |
|||
=== Install MNE Python === |
|||
conda install mamba -y |
|||
mamba create -n tutorial_stats conda-forge::mne conda-forge::datalad -y |
|||
conda activate tutorial_stats |
|||
=== Download the data === |
|||
Will Update soon with appropriate paths etc. |
|||
git clone ------- data repo |
|||
cd ---- |
|||
datalad get ./* |
|||
=== Additional MEG Stats Links === |
|||
https://mne.tools/stable/auto_tutorials/stats-sensor-space/10_background_stats.html |
|||
https://eelbrain.readthedocs.io/en/stable/getting_started.html |
|||
https://neuroimage.usc.edu/brainstorm/Tutorials/Statistics |
|||
https://www.fieldtriptoolbox.org/tutorial/eventrelatedstatistics/ |
|||
Latest revision as of 12:58, 23 March 2023
!!UNDER CONSTRUCTION!!
Tutorial Session
Recording Download: MNE & AFNI Group Analysis Tutorial (mp4)
Afni Prep
Install Afni on computer:
https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/background_install/install_instructs/index.html
Statistical Processing in AFNI
#! /bin/bash # First things first: Good practice to convert .nii files to afni .HEAD .BRIK format: 3dcopy mydataset.nii myafnidataset # Here the data have been converted to common space (+tlrc) but if not can be done in afni with adwarp # Example: One Sample T-test on alpha band log ratio of face power and shape power # Why log-ratio? log(faces/shapes) = log(faces) - log(shapes) ; log attentuates outliers , normalizes distribution. # First make a list of subjects for test: ls *_7_13_*lograt*.HEAD > alpha_list # Then run one sample T-test 3dttest++ -setA `cat alpha_list` -prefix alpha_ttest # Optional: add effect size to output 3dMean -prefix alpha_mean `cat alpha_list` 3dMean -sd -prefix alpha_std `cat alpha_list` 3dcalc -prefix alpha_effectsize -a alpha_mean+tlrc -b alpha_std+tlrc -expr 'a/b' 3dbucket -prefix alpha_ttest_effectsize alpha_ttest+tlrc alpha_effectsize+tlrc 3drefit -sublabel 2 "effectsize" alpha_ttest_effectsize+tlrc # Could do a paired T-test between faces and shapes instead of log-ratio ls *_7_13_*shape*.HEAD > alpha_shape_list ls *_7_13_*face*.HEAD > alpha_face_list 3dttest++ -setA `cat alpha_face_list` -setB `cat alpha_shape_list` -paired -prefix alpha_paired_ttest # Can add covariates to T-tests. # Can do mixed-effects ANOVAs and other fancier stuff
MNE Python
Install MNE Python
conda install mamba -y mamba create -n tutorial_stats conda-forge::mne conda-forge::datalad -y conda activate tutorial_stats
Download the data
Will Update soon with appropriate paths etc.
git clone ------- data repo cd ---- datalad get ./*
Additional MEG Stats Links
https://mne.tools/stable/auto_tutorials/stats-sensor-space/10_background_stats.html https://eelbrain.readthedocs.io/en/stable/getting_started.html https://neuroimage.usc.edu/brainstorm/Tutorials/Statistics https://www.fieldtriptoolbox.org/tutorial/eventrelatedstatistics/