eelbrain.testnd.LMGroup.column_ttest¶
-
LMGroup.
column_ttest
(self, term, return_data=False, popmean=0, *args, **kwargs)¶ One-sample t-test on a single model column
Parameters: - term : str
Name of the term to test.
- return_data : bool
Return the individual subjects’ coefficients along with test results.
- popmean : scalar
Value to compare y against (default is 0).
- tail : 0 | 1 | -1
Which tail of the t-distribution to consider: 0: both (two-tailed); 1: upper tail (one-tailed); -1: lower tail (one-tailed).
- samples : None | int
Number of samples for permutation cluster test. For None, no clusters are formed. Use 0 to compute clusters without performing any permutations.
- pmin : None | scalar (0 < pmin < 1)
Threshold for forming clusters: use a t-value equivalent to an uncorrected p-value.
- tmin : None | scalar
Threshold for forming clusters.
- tfce : bool
Use threshold-free cluster enhancement (Smith & Nichols, 2009). Default is False.
- tstart, tstop : scalar
Restrict time window for permutation cluster test.
- mintime : scalar
Minimum duration for clusters (in seconds).
- minsource : int
Minimum number of sources per cluster.
Returns: - result : ttest_1samp
T-test result.
- data : Dataset (only with
return_data=True
) Dataset with subjects’ coefficients.
Notes
Performs a one-sample t-test on coefficient estimates from all subjects to test the hypothesis that the coefficient is different from popmean in the population.