Our new paper is out! It offers a tool to assess collinearity impact on contrast estimates *and* uses simulations + MID data to show how common collinearity avoidance strategies can bias results. Huge thanks to @russpoldrack.org , M Demidenko, and the ABCD folks. 🔗 direct.mit.edu/imag/article...

Do you ever wish you could just use python to pull together the files and code for running FSL's randomise? Me too! I made this: github.com/jmumford/ran... It will even replace the numbers in the file outputs with contrast names of your choosing (and replace corrp with 1minusp).

Interested in practical tips for assessing collinearity and why common fixes might not help? Come to the #OHBM2025 oral session Friday at 11:30AM (P2)! I’ll share simulation results and @demidenko.bsky.social will present real data. Also, check out my poster Thursday (1051)!

chng.it/gmWgmwwz6n The Open Science Room needs your help!

Following a lot of hard work and dedicated effort from countless parties, our textbook providing a hands-on introduction to analyzing network data is now available for pre-order from Cambridge University Press www.cambridge.org/core/books/h...

Shameless plug for a useful tool tucked away in Appendix B of our preprint. A VIF calculation for *contrasts*, cVIF. A foolproof way to assess how collinearity is impacting what you're actually interested in! Code available on GitHub! www.biorxiv.org/content/10.1... github.com/jmumford/vif...

Setting up an fMRI model and getting hit with collinearity errors? Been there! 😢 Try removing regressors? Orthogonal regressors? Other tricks to resolve collinearity errors? Guess what—those fixes might make things worse. We explore why and propose recommendations. www.biorxiv.org/content/10.1...