Single-level and multi-level mediation analyses for any kind of data, with bootstrap-based significance testing. Neuroimaging-oriented functions allow for mediation effect parametric mapping (mapping of mediation effects across the brain) and multivariate mediation.
Thanks for the convenient MediationToolbox you provided us.
I only have one trial(resting state fMRI) per subject, as mentioned in " High-dimensional multivariate mediation with application to neuroimaging data" and "multiple brain networks mediating stimulus-pain relationships", I think PDM_toolbox rather than mediation_toolbox should be the right one to use, right?
The function used are:
pdm =multivariateMediation(xxx',yyy',mm','B',20,'svd','nPDM',3,'bootPDM',1:3,'jointPDM',false,'Bsamp',100,'save2file','PDMresults.mat');
[obj,figh] = plotPDM(pdm,dat);
Dear Prof.Wager,
Thanks for the convenient MediationToolbox you provided us.
I only have one trial(resting state fMRI) per subject, as mentioned in " High-dimensional multivariate mediation with application to neuroimaging data" and "multiple brain networks mediating stimulus-pain relationships", I think PDM_toolbox rather than mediation_toolbox should be the right one to use, right?
Besides, when i use the example data in 'https://github.com/canlab/MediationToolbox/blob/master/Mediation_walkthrough/mediation_example_script_1.m' and use resampled MNI152_T1_2009c as brainmask, there is one error in matlab, after dubugging, i found it comes from the comparison of full volume and non-zero volume dimension in reparse_contiguous(), could you give me some ideas of how to fix this?
The function used are: pdm =multivariateMediation(xxx',yyy',mm','B',20,'svd','nPDM',3,'bootPDM',1:3,'jointPDM',false,'Bsamp',100,'save2file','PDMresults.mat'); [obj,figh] = plotPDM(pdm,dat);
Much appreciated!
Best wishes, Peng