When a non-hierarchical cluster analysis is carried out, the order of observations in the data file determine the clustering results, especially if the data set is small (i.e, 5000 observations). To deal with this problem I usually performed a random reorder of data observations. My problem is that if I replicate the analysis n times, the results obtained are different and sometimes these differences are great.
How can I deal with this problem? Maybe I could run the analysis several times and after consider that one observation belong to the group in which more times was assigned. Has someone a better approach to this problem?