Mauricio and Ricardo:
Mauricio, good to hear from you too!!
As often happens on the list, we can at times use the same words but mean different things.
To clarify, I was thinking of inferential as opposed to descriptive statistics in my previous reply. And, I was thinking of statistics as a tool to analyze research data rather than as a stand-alone research method. Therefore, perhaps my assumptions were answering something a little different from what you were questioning. If so, I'm sorry.
As your (Mauricio's) post suggests, using statistics (or anything else) to infer INDIVIDUAL PREFERENCES across populations is dangerous because personal preferences are inherently unstable. (Adapting Mauricio's analogy) I may want ham and cheese for lunch right now, but in 30 minutes I may have changed my mind and want soup instead. On the other hand, things like visual perception and human cognition are more generalizable across populations and making inferences based on those relatively stable operations should be more valid. In short, the STABILITY OF THE PHENOMENA is important to consider when making inferences.
Some of your (Ricardo's) comments in your Jan 13 post suggest to me the importance of study design rather that the statistical means use to help understand the study. For example, good study design will be critical in determining whether "a choice occurred by chance or due to a deliberately proposed change by a designer." My takeaway here is a cliché: good statistics cannot make up for bad study design. I'm not saying that you described bad any study designs (other than perhaps your intentional reference to some of Tinker's work). GOOD STUDY DESIGN, one that accurately explores the hypothesis/question of interest, is an essential skill, a difficult and challenging skill I still work on with each study.
I, and I infer (sorry, I couldn't resist) perhaps other design researchers as well, need better exposure to, and more skill at, the various methods you explained: cluster analysis; logistic regression; factorial analysis; and others. In our 2014 paper we used odds-ratio. I would not have known about "odds-ratio" if not for my colleague Amy.
I'd welcome being at least a fringe part of a group of design researchers working to improve our field's appropriate use of statistical methods. An on-line course or consulting group are even possibilities. In my last post I mentioned Cincinnati Children's Hospital and the Research Foundation. They have a Division of people that provides statistical support to the other researchers. Advanced in research as their researchers are, they are not all equally skilled at statistical analysis and this Division helps insure appropriate methods are designed-into studies at the start. Perhaps design research would benefit from some group of experts or consultants on-line that could provide a similar service to design researchers worldwide. Ricardo, perhaps you are the one to organize this!
Best...
Mike Zender
University of Cincinnati
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