[Eeglablist] Statistically determining earliest time point of difference between two single trials

Stephen Politzer-Ahles politzerahless at gmail.com
Mon Sep 2 07:00:28 PDT 2019


Hi Kaelasha,

This is described in the paper by Groppe and colleagues (2011):
https://onlinelibrary.wiley.com/doi/full/10.1111/j.1469-8986.2011.01273.x.
Crucially, if you want to know when an effect starts to be significant,
you'll want to use the test with strong control of family-wise error rate
(the non-cluster-based test), not the cluster-based test (which only has
weak control of family-wise error rate, and doesn't license inferences
about when an effect starts to be significant).

This test is implemented in the Mass Univariate ERP Toolbox, which works
with EEGLAB.

Best,
Steve

---
Stephen Politzer-Ahles
The Hong Kong Polytechnic University
Department of Chinese and Bilingual Studies
http://www.mypolyuweb.hk/~sjpolit/
<http://www.nyu.edu/projects/politzer-ahles/>


On Mon, Sep 2, 2019 at 4:25 PM Kaelasha Tyler <kaelasha.tyler at gmail.com>
wrote:

> Hi all,
>
> I am wanting to determine the earliest time point at which a statistically
> significant deviation between two matched trial ERPs can be detected,
> looking at single trials.
>
> I have looked across this discussion forum but haven't seen any thread
> that actually explains how to do this (if possible) in EEGlab.
>
> Any pointers anyone?
>
> I am replicating a study which used sample-wise truth-label switching Monte
> Carlo permutation tests. However for my purposes it wouldn't have to be the
> exact same statistical procedure as in this study, as long as I can achieve
> the same statistical ends.
>
> Thanks in advance,
>
> Kaelasha
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