News and Updates
Longitudinal Structural Equation Modeling is an extension of our prior three-day course on latent curve modeling. In response to requests from participants, we’ve expanded this course into a full five-day workshop. In addition to covering introductory and advanced topics in latent curve modeling, we now also include material on longitudinal measurement modeling, autoregressive cross-lagged panel models, and latent change score analysis, providing a complete treatment of longitudinal modeling approaches within the SEM framework.
Cluster Analysis and Mixture Modeling is an entirely new five-day workshop focused on the application and interpretation of statistical techniques designed to identify subgroups within a heterogeneous population. This course is being developed in partnership with and will be co-taught by Doug Steinley, a professor of quantitative psychology at the University of Missouri who has published extensively on these topics and is the current editor of Journal of Classification. Doug is a remarkable writer and speaker, and we are excited about this joint offering.Read More
An important concept to understand with multilevel data is the distinction between between-group and within-group effects. For instance, larger animal species (elephants) tend to live longer than smaller species (ducks); this is the between-group effect of size on life expectancy. Within a species, however, larger individuals (big ducks) tend to live less long than smaller individuals (small ducks); this is the within-group effect of size on life expectancy. Recently, Shankar Vedantan described another example on NPR: people report being happier making $50 for a project if their co-workers are making $40 versus making $60 for the same project if their co-workers are making $70. See the full story.Read More
Although a bit old school, listservs such as SEMNET (for latent variable models) and the Multilevel Discussion List remain useful resources when grappling with quantitative modeling issues. You can search the archives to see if your question has come up before or post a new question to obtain fresh feedback / opinions from list members. Quick tip: use the “receive digest” setting to avoid having your inbox flooded with listserv posts. (more…)Read More
Something that has come up often recently: When participants provide responses to a set of items or prompts, such as words, faces, or pictures, these items may represent a sample from a broader universe of possible items (e.g., a sampling of words from the lexicon). Responses may then best viewed as reflecting two crossed random factors, items and persons. A couple of nice papers on how to fit cross-classified random effects models to this kind of data are Baayen et al (2007) and Locker et al (2007).Read More