I have been wading through the many discussions on outliers on this site but I am still unfortunately having difficulty determining what to do with my data set.
My study consists of a simple pre-post test setup whereby i conduct 6 tests prior to and 6 tests following my treatment. The purpose of the repeated tests is to decrease the effect of anomalous performance on the results and increase the sensitivity. We therefore expect that generally 1 or 2 of these 6 tests to be a bit different to the other 4. At present I've been removing abnormal scores by identifying those results that lie outside +/- 1 standard deviation. This practice has proven somewhat satisfactory (in that it detects most of those scores that upon visible inspection appear anomalous), however I read more and more that the use of standard deviation is not appropriate for determining outliers, and sometimes I've found that the scores deemed as outliers are not always those that appear the most anomalous.
Therefore I'm wondering whether you can offer any suggestions as to how i can improve/better standardise my selection process? Is my current method acceptable? If so, do you know of any published material that has validated this approach (or does this approach have a name that i could google?) Alternatively, would the use of an interquartile range approach using the median value prove more satisfactory?