I have to analyse data from a marketing study. I will use SPSS. The questionnaire will look like this:
Q: Imagine Situation X. Select 1-3 Criteria from the list that best describe your feeling.
I want to perform cluster analysis to find out which respondents have similar feelings and what are the most often selected feelings in each cluster. The output is basically a set of binary codes (present vs absent). The categories are asymmetric: In other words, a 0-0 match should not necessarily be considered similar.
From this incredibly helpful post, I understood, that hierarchical cluster analysis, using a dice measure should work in my case. However, I also understood that it is not suitable for a large number of samples due to performance issues. (My sample size is 1500.)
- Is my way of thinking correct?
- Would you still recommend using hierarchical clustering?
- If no, what else would you recommend?
- If yes, how bad will the performance be / how long will it take SPSS to run this? (I don't have the dataset yet, so I can't try it out.)