LIMO tools were developped with EEGLAB functions for reading files and do some vizualization. Simply unpack the repository into the EEGLAB plugin folder. It can be called via STUDY using the EEGLAB developper version.
All the statistics are performed internaly and therefore our tools can be used as stand alone. After setting the path to the toolbox, you can call statistical functions and vizualize results. Check the wiki on how to use each function for your analyses
The next frontiers ... there are no reasons why we could not integrate. We are actively looking for new contributors who want to make this happen.
Flexible Models through a hiearchical approach
Remove influence of outliers
Use modern resampling techniques
The prefered way to report bugs is to submit an issue on github, but emailing us is fine too. We'll try to adress your problem as soon as possible
The fastest way to get acknowledged is to add your name to our contributor list
Found a bug and fixed it! submit the pull request to we can merge it - add your name on our contributor lists
There are always new methods to use, maybe you designed one?. Get in touch to integrate it to the list of tools
There many ways to contribute, including documentation and testing, check it out
one sample t-test, two-samples t-tests, paired t-tests, ANOVA, ANCOVA, repeated measures ANOVA, single and multiple regressions, and more to come.
For each subject, code each condition (e.g. 4 conditions in a 2x2 design). At the group level, compute a repeated measures ANOVA with N factors (eg. 2x2).
These are statistical procedures that work for non-normal distributions and are this not affect by outliers.
To compute clusters at the channel level, one must declare which channels are neighbours, i.e. which channels we want to see grouped together.
Results must be interpreted based on the statistical method used for inference, cell-wise or cluster-wise