On Jan 10, 2014, at 8:15 PM, Daniel P. Bliss wrote: > I think this question was based on a misinterpretation of what the > event-related analysis actually does. I was assuming that it conducted a > separate classification analysis for each timepoint, but now I'm inferring > that it conducts a single analysis, treating the timepoints as independent > features. Is that true?
Not necessarily independent, but yes, data from different timepoints is used in the analysis. > Is there a way to automate separate analyses for different timepoints in > PyMVPA? Yes, but it depends a bit on what type analysis you want to do. I assume you have a dataset ds with trials that have N timepoints each. Add a sample attribute, say 'time_in_trial', and assign to each sample a value from 1 to N. Then do ds_splits=split_by_sample_attribute(ds, 'time_in_trial') and run your analysis separately for each dataset in ds_splits, e.g. ds_results=[] for ds_split in ds_splits: # your code here to get ds_result ds_results.append(ds_result) result=hstack(ds_results) _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
