I recently came across this article by David Greenberg in the Journal of Developmental and Life Course Criminology. I have previously seen an early draft, and I am glad to see it finally published! (Should have been published a long time ago as the version I saw was pretty good, but I have no idea why it has not). Greenberg shows how to use standard multilevel modeling with normal distributed parameters to test typological theories. The procedure is actually not very complicated: estimate a random effects model, use empirical Bayes to get point estimates for each person’s intercept and slope(s), and explore the distributions of those point estimates using e.g. histograms. And no: those empirical Bayes estimates do not have to be normal distributed! You need to decide for yourself (preferably up front) what it takes for these distributions to be in support of your favourite typology, so it requires a bit of thinking. This can all be done in standard statistical software, only requiring knowing a little bit about what you’re doing. It would be really nice to see previous publications using group-based models reanalyzed in this way.
The article also discuss a number of related modeling choices which are highly informative. So far, I have only read the published version of the article very quickly, and I need to read it more carefully before I fully embrace all arguments, but I might very well end up embracing it all.
I have noticed that it has been claimed in the literature that models assuming normal distributed random effects cannot test for the existence of subpopulations. Well, it is the other way around.
The post Criminological progress! appeared on The Grumpy Criminologist 2016-07-04 12:00:12 by Torbjørn.