**y** (*NDVar*) – Dependent variable.

**x** (*categorial** | **NDVar*) – Model containing the cells which should be compared, or NDVar to which
`y`

should be compared. In the latter case, the next three parameters
are ignored.

**c1** (*str** | **tuple** | **None*) – Test condition (cell of `x`

). `c1`

and `c0`

can be omitted if
`x`

only contains two cells, in which case cells will be used in
alphabetical order.

**c0** (*str** | **tuple** | **None*) – Control condition (cell of `x`

).

**match** (*categorial*) – Units within which measurements are related (e.g. ‘subject’ in a
within-subject comparison).

**sub** (*index*) – Perform the test with a subset of the data.

**ds** (*Dataset*) – If a Dataset is specified, all data-objects can be specified as
names of Dataset variables.

**tail** (*0** | **1** | **-1*) – Which tail of the t-distribution to consider:
0: both (two-tailed, default);
1: upper tail (one-tailed);
-1: lower tail (one-tailed).

**samples** (*int*) – Number of samples for permutation test (default 10,000).

**pmin** (*None** | **scalar** (**0 < pmin < 1**)*) – Threshold for forming clusters: use a t-value equivalent to an
uncorrected p-value.

**tmin** (*scalar*) – Threshold for forming clusters as t-value.

**tfce** (*bool** | **scalar*) – Use threshold-free cluster enhancement. Use a scalar to specify the
step of TFCE levels (for `tfce is True`

, 0.1 is used).

**tstart** (*scalar*) – Start of the time window for the permutation test (default is the
beginning of `y`

).

**tstop** (*scalar*) – Stop of the time window for the permutation test (default is the
end of `y`

).

**parc** (*str*) – Collect permutation statistics for all regions of the parcellation of
this dimension. For threshold-based test, the regions are disconnected.

**force_permutation** (*bool*) – Conduct permutations regardless of whether there are any clusters.

**mintime** (*scalar*) – Minimum duration for clusters (in seconds).

**minsource** (*int*) – Minimum number of sources per cluster.