- LMGroup.column_ttest(term, return_data=False, popmean=0, *args, **kwargs)
One-sample t-test on a single model column
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 (scalar) – Restrict time window for permutation cluster test.
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.
result (TTestOneSample) – T-test result.
data (Dataset (only with
return_data=True)) – Dataset with subjects’ coefficients.
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.