Vectorized t-test for for brain imaging phenotypes

Perform independent sample and paired sample t-tests between two numerfor differences between means of brain imaging phenotypes for a categorical variable. For most scenarios, the user does not need to call this function directly. This function will be called internally from bstr_ttest()

ttest_vec(X1, X2, group_var, paired = FALSE)

Arguments

X1: matrix of dimensions ( $N1 x T$ ), where $N1$ = number of subjects and $T$ = number of vertices/voxels.
X2: matrix of dimensions ( $N2 x T$ ), where $N2$ = number of subjects and $T$ = number of vertices/voxels.
group_var: Categorical variable name. This should be present in the demographics csv file associated with bstr_data.
paired: logical; is TRUE if group_var contains matching (dependent) samples. The default value is FALSE.

Details

For an independent samples t-test $N1$ not equal to $N2$ . For a dependent (paired) samples t-test, $N1 = N2$ . The degrees of freedom are calculated using the Welch–Satterthwaite approximation by default. bstr_data can be of the type "sba", "tbm", or "roi".