mne.stats.ttest_ind_no_p

mne.stats.ttest_ind_no_p(a, b, equal_var=True, sigma=0.0)

Independent samples t-test without p calculation.

This is a modified version of scipy.stats.ttest_ind(). It operates along the first axis. The sigma parameter provides an optional “hat” adjustment (see ttest_1samp_no_p() and 1).

Parameters

aarray_like

The first array.

barray_like

The second array.

equal_varbool

Assume equal variance. See scipy.stats.ttest_ind().

sigmafloat

The regularization. See ttest_1samp_no_p().

Returns

tarray

T values.

References

1

Gerard R. Ridgway, Vladimir Litvak, Guillaume Flandin, Karl J. Friston, and Will D. Penny. The problem of low variance voxels in statistical parametric mapping; a new hat avoids a ‘haircut’. NeuroImage, 59(3):2131–2141, 2012. doi:10.1016/j.neuroimage.2011.10.027.

mne.stats.ttest_1samp_no_p mne.stats.f_oneway