The idea is that you convert the Munsell readings to spatial coordinates in the Munsell color space and then perform spatial or statistical analyses on the coordinates, which are interval scale variables. For the kinds of hypotheses I wanted to test--whether the ceramic colors from one houselot or cluster of houselots were the same as those from another--I decided that logistic regression was probably the right technique because:
- the dependent variable (the provenience, i.e., the houselot of cluster of houselots) was a categorical variable; and
- the data were demonstrably non-normal, thus eliminating linear discriminant analysis.
Apparently, the real lesson here is that if you think about something for 20 years, you just might figure out the answer, although I hasten to point out that during those 20 years I studied quantitative techniques pretty intensively. I wasn't just sitting on the beach pondering the problem solely in thought; I was actually educating myself--howsoever unsystematically--about the general topic of mathematics in archaeology. Nevertheless, there is a push among university administrators to systematize and quantify scientists' goals and productivity. So, if I put down on my annual assignment that I'm going to study how to analyze Munsell colors, presumably I'm expected to produce the article in the year it's listed. If you take into account how long it took to devise the original research design, excavate the artifacts, and record the Munsell colors, this article has been in the works for 25 years! Should I submit a 25-year plan as part of my annual assignment? If I do, I can probably say anything I want because I'll almost certainly be dead in 25 years.
Here is the reference, linked to the article:
Ruck, Lana and Clifford T. Brown (2015). Quantitative analysis of Munsell color data from archeological ceramics. Journal of Archaeological Science: Reports 3:549-557.
Just in case the link doesn't work for any reason, here is the URL: http://www.sciencedirect.com/science/article/pii/S2352409X15300730#
As always, comments welcome.