One of the problematic things with multilevel modeling is that it can be somewhat tricky to determine if and when random effects are important. Ideally, you would want to use a P value but it’s not particularly easy to do so with…

One of the more common applications of multilevel modeling within political science is the use of a repeated or rolling cross-section of data instead of a true panel structure. In this set up you have a new pool of observations that…

Here lies my current list of books on multilevel, longitudinal, and panel data modeling. I’ve broken them down into rough categories but there’s a lot of heterogeneity within groups here. I’m explicitly avoiding including articles on this list because there are…

Last January, I created a reading list for myself for the upcoming year. It turns out that just creating the list doesn’t actually mean that you’ll read everything on it and I managed to get through about a third of…

Say that you want to model ordinal change in status (e.g. a Likert scale) over time between two or three time periods. How do you go about it? I had to put a decent amount of thought into this problem…

Probably the most common technique for dealing with repeated observations in economics and a lot of the social sciences is to segregate between group and within group variability and only look at the within group effects of explanatory variables on…

One of the things that had the biggest impact on my early development as a methodologist was reading Kenneth Train’s book Discrete Choice Methods with Simulation. It’s available for free as a PDF on his website. You should read it. Really.  The focus…

Missing Data

A few weeks ago I briefly mentioned Craig Enders in a previous post by way of citing his excellent book chapter in the Sage Handbook of Multilevel Modeling. At this point, I’m planning to read just about everything he writes on…