[Mne_analysis] Goodness of fit statistic for TF-MxNE solution?

[Per Arnold Lysne]

Hi Alex,

    R^2 would be perfect, since it is easy to interpret and has the accompanying F-test. However, R^2 only applies to a single outcome variable, being calculated as SS_reg/SS_total. This is where I turned to Wilk's Lambda, being the multivariate extension of R^2, or det(SSCP_res)/det(SSCP_total). Unfortunately the determinants cannot be calculated on data that is not full rank, which leads to the questions I am asking about PCA in the other thread.

    Am I missing something? I am not operating on the whitened data.

    Agreed that butterfly plots are an excellent visual verification of fit, and I am already producing them.

    Thanks again,

-Per

________________________________________
From: mne_analysis-bounces at nmr.mgh.harvard.edu <mne_analysis-bounces at nmr.mgh.harvard.edu> on behalf of Alexandre Gramfort <alexandre.gramfort at telecom-paristech.fr>
Sent: Friday, October 3, 2014 3:30 AM
To: Discussion and support forum for the users of MNE Software
Subject: Re: [Mne_analysis] Goodness of fit statistic for TF-MxNE solution?

hi Per,

>     Sorry for the delay on this question. I would like to report a goodness of fit between the evoked response (at the sensors) derived from my experimental data, and the evoked field (at the sensors) as modeled by the tf-mxne solution. I often see this associated with dipole fits (on the mne_analyze dipole list?) and it is usually reported at "Goodness of Fit" as a percentage. Is this the Chi-Sq you mention, and do you know of a useful reference to it?

maybe somebody else can point you to some refs when using dipole fits.

for tf-mxne GOF makes sense on whitened data unless you have one
sensor type (eg. gradiometers). I am not even sure how neuromag graph
reports GOF for combined sensors.
Any hint from somebody?

so option one is to report GOF or R2 coef of determination on let's
say only gradiometers.
or compute these metrics on whitened data. I'd also recommend you show
the butterfly
plots of explained data. It is a nice way to visually demonstrate that
your sources
explain the data correctly.

HTH
Alex

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