@Tahariet Sharon It is true that multcompare cannot work with input from vartestn. A frustration with multcompare is that it cannot work as a standalone test; that is, it cannot receive as input a matrix of column data and perform a pairwise comparisons test on that data. That's unfortunate, in my view. However, multcompare can receive as input a stats object created from anova1.
Below is a script that performs a pairwise comparisons test on a matrix of column data. The script loads some test data, creates a stats object from that data, then passes that object in to multcompare. Mission accomplished!
The 16x4 test data are in testdata.txt, which is attached. The file contains 16 marks on 4 tests. The last column of output produced by multcompare is the p-value for the hypothesis test that the corresponding mean difference is not equal to 0 for the pairs tested in that row. As seen below, the marks were significantly different (p < .05) between tests 1 and 3 and tests 2 and 3.
multcompare uses the Tukey-Kramer test by default, but other tests (e.g., Bonferroni) can be specified via the 'CType' option.
% load test data: 16 marks on 4 tests
y = readmatrix('testdata.txt'); % 16x4
% do the anova -- just to get a stats object
[~, ~, stats] = anova1(y, {'t1' 't2' 't3' 't4'}, 'off');
% pass stats object into multcompare (p-value in last column of output)
multcompare(stats, 'display', 'off')
