quick reply, so might be incomplete
On Tue, 09 Jul 2013, Derek Huffman wrote: > Hello all, > I�am using MCNullDist with enable_ca=['dist_samples'] for significance > testing. I am wondering, for subjects with differing number of trials per > run (but balanced targets within each run) is the > .null_dist.ca.dist_samples returning the correct average accuracy (that > is, number_correct / total_number_of_trials, akin to > .ca.stats.percent_correct) or is it simply averaging over each > cross-validation assuming equal number of trials per run (akin to > np.mean(cv_results))? I am assuming it is the former but would appreciate > your confirmation. MCNullDist doesn't average anything -- it just collects samples of whatever measure you are computing. If it does averaging across splits (postproc=mean_sample()) then that is what it would "operate on". but your usecase is also interesting because of the differing number of trials per functional run, so I expect chance distribution possibly diverging even more from a "theoretical" (bi|multi)nomial one in comparison as if you had equal number of samples across runs. share your observations happen you find them interesting. Cheers, -- Yaroslav O. Halchenko, Ph.D. http://neuro.debian.net http://www.pymvpa.org http://www.fail2ban.org Senior Research Associate, Psychological and Brain Sciences Dept. Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755 Phone: +1 (603) 646-9834 Fax: +1 (603) 646-1419 WWW: http://www.linkedin.com/in/yarik _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
