Hope you’re doing well in these challenging times,
I was checking the chapter 34 about regression in the ANTS book,
I have a couple of questions regarding the implementation in the Matlab code,
I see a small difference in the treatment between total power and the independent variables: the RTs and alpha power. The IV are zscored, and the total power is ranked with tiedrank. These functions normalize data, so maybe there are no big differences between the two. But I wonder if there is any reason to use one or another for the data or for the regressors,
More theoretically, how would you deal with baseline-corrected data? I mean suppose I have found an change of alpha power between an incongruent and a congruent condition for an experiment X. Then I want to dig in this effect and see if I see a correlation (or a regression) between alpha power and some regressor such as reactions times and trial-level behavioral responses. For the classical analysis I usually run some t-tests or ANOVA on baseline-corrected data. How would you do for correlations or regression at the trial level?
Many thanks in advance for your insights,