[Eeglablist] LIMO toolbox - difference between clusters surviving correction with R^2 vs. F statistics

[Makoto Miyakoshi]

Dear Cyril,

When you have time, could you please take a look for your comment?

Makoto

On Thu, Jul 30, 2020 at 12:42 PM Dan Kleinman <kleinman at gmail.com> wrote:

> Hello All,
>
> I have a question about results obtained using the LIMO toolbox (v2.0).
> Specifically, I performed an analysis in two different – but, I think,
> equivalent – ways, and obtained substantially different results depending
> on how it was conducted. I am wondering if others who have experience using
> (or programming) the toolbox could please shed light on why the results are
> different.
>
> At the first level, I coded for (binary) trial condition using a single
> continuous variable (no categorical variables) for all participants. At the
> second level, I conducted a Regression analysis to identify spatiotemporal
> clusters at which a continuous between-subjects variable correlated
> significantly with the effect of condition. Importantly, *I only entered
> one between-subjects variable at this stage*.
>
> There are (at least) two ways to view the results:
> (1) Show clusters at which r^2 is significant (by selecting R2.mat; “Model
> fit")
> (2) Show clusters at which F is significant (by selecting
> Covariate_effect_1.mat; “F test for a continuous regressor")
>
> If I do not apply a correction (MC Correction=None), the cluster maps with
> uncorrected thresholds look identical (as I would expect with only one
> regressor). However, if I apply a correction (MC Correction=Clustering),
> method (1) yields a significant cluster but method (2) does not. This
> pattern holds true across a number of different datasets, in that method
> (1) often yields a significant result even when (2) does not and only a
> single regressor is used.
>
> Is this expected behavior? If so, how should I interpret the r^2 cluster
> results vs. the F cluster results with one regressor?
>
> Many thanks,
> Dan Kleinman
>
> —
> Daniel Kleinman, Ph.D.
> Postdoctoral Fellow
> Haskins Laboratories
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