Description Usage Arguments Value Author(s) Examples
Compiled fast t-tests on matrices. Takes a binary matrix X with zero and non-zero values, and a matrix Y of continuous values. Computes the t-test on each Y column using the respective X column to define the two groups. If Y is a matrix with one column, that column is used to test with grouping derived from every column in X. This function is used in LESYMAP with a binarized X matrix derived from lesioned voxels in the brain.
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X |
binary matrix of voxels (columns) for all subjects (rows). |
Y |
matrix of behavioral scores of same size as X or a matrix with a single column. |
computeDOF |
(default=true) chooses whether to compute degrees of freedom. Set to false to save time during permutations. |
varEqual |
(default=true) chooses whether to compute Student t-scores (true) or Welch d-scores (false). The only difference is the assumption on variance which for t-scores must be satisfied. This assumption is often violated in some voxels, and the use of Welch (varEqual=false) is recommended for more accurate results. |
List with two vectors:
statistic
- Student T or Welch D
df
- degrees of freedom
Dorian Pustina
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