The Q-Test is what is called a outlier test. It compares the suspected point with the total range. As you start eliminating points your range decreases. As a results, if you repeat the process again with the new range your chances of eliminating another point increase, even if it is not an outlier of the original data set. As a result it is possible, and quite common for it to mathematically eliminate the entire data set if you repeat it. If you have two questionable points, one at the top of the range and one at the bottom, apply the q-test to both of them and see which one has the greatest confidence in throwing that one away, and discard only that one.