With Session 4, we finally get into heavy usage of MKTR software. The session comprises two broad topics - Perceptual Mapping and Data Reduction. It promises to be rich in tools, concepts and learning in a variety of ways - from a data visualization standpoint to map-interpretations to demographic-basis segmentation.
In the first broad topic - Perceptual mapping - we learn how to invoke, handle and exploit two types of perceptual maps - Attribute based Joint-space maps and similarity based MDS maps.
Admittedly, I couldn't readily locate a canned package in R that does Joint Space maps. But the ingredients are all there, so I wrote up my own home-brew R code for joint space maps. The output tallies nicely with MEXL output, BTW.
To my knowledge, MEXL doesn't do MDS (multi-dimensional scaling) and so, we'll have to rely solely on R for this one.
For the second broad session topic - Data Reduction - we use Factor Analysis. And in factor analysis, R does pretty much everything you can ask for - from principal components extraction to principal axis factoring to singular value decompositions of arbitrary matrices to enabling every factor rotation scheme you can imagine. In contrast, (from what I have seen so far), MEXL does only common factor analysis, that too sans any factor rotation and with little in the way of guidance for selecting the optimal no. of factors. Oh, and it limits the maximum no. of observations your dataset can have (to 200, from what I recall).
Last but not least, pls expect your homework for this session to be on the heavier side only. I'm hoping you'll choose R for this project. In at least one Q, you won't have the MEXL option available to you anyway. I'll put up the classwork as well as homework datasets and the R code for it in a separate post.
Sudhir
Professor, if I remember correctly, we have explored joint space maps (which can be done on both R and MXEL) but not MDS, the other kind of perceptual map, possible in R but not in MXEL, as you state above.
ReplyDeleteMDS is also possible in SPSS and we did do an exercise based on it in the ENDM course. You can also probably look at exposing students to this technique via SPSS as part of your course next year onwards.
I find that the analyses we do in MKTR are slightly deeper than the ones we do in ENDM. So, it can really help students who expect to use these tools in their jobs going forward.
Regards,
Shouri Kamtala
Oops, I posted a bit too soon. Even though I have read the post which discusses R codes for session 4, it completely slipped my mind that there is tiny code already tucked in there for MDS which we didn't do in class.
ReplyDeleteThanks, Shouri.
ReplyDeleteThe reason I don't use SPSS (and I used it once as the primary software platform for MKTR last year - is licenses. The school only gives 2-weeks of trial student licenses. That severely constrains what and when I can cover in terms of topics and what students can do for their projects.
I'm relieved my move to R has not boomeranged on me (yet) and that students have sort-of taken well to this great platform. Unfortunately, R was not originally designed for lay person usage and it shows. The R platform remains mostly confined to the research community which developed it in the first place (and not industry).
Sudhir