News and Updates
Often the most interesting research question is not whether a relationship between two variables exists but rather under what conditions the relationship holds. Put in statistical terms, we are often less interested in main effects than we are in interactions or moderation. An interaction implies that the magnitude of the relation between two variables differs as a function of some third variable. For example, there might be a positive relation between anxiety and alcohol use in adolescents, and this is particularly salient for girls compared to boys. When an interaction exists, we must probe and plot the conditional relations to fully understand the nature of the effect. To help with this, we have collaborated with Kris Preacher (who is an Associate Professor of Psychology at Vanderbilt University) to develop a set of online utilities to help probe interactions for multiple regression, multilevel models, and latent curve models. These utilities are freely accessible and are extremely helpful in understanding a variety of interaction effects that might be encountered in practice.Read More
The differences between Bayesian and Frequentist perspectives on hypothesis testing can quickly become quite complex. We recently ran across a series of excellent essays in the APS Observer written by current Association for Psychological Science President C. Randy Gallistel that provides a gentle yet clear introduction to Bayes estimation. His highly accessible essays are titled “Bayes for Beginners”, and the first is subtitled “Probability and Likelihood”Read More
There is increasing attention paid to the so-called “reproducibility crisis” in psychology. There have been a number of high-profile reports of failures to reproduce many classic findings in psychology. Although this is of course a critically important topic within the social sciences, a recent article by Samantha Anderson and Scott Maxwell in Psychological Methods argues that we must take a broader perspective on reproducibility than simply replicating the single outcome of a given experiment. In “There’s More Than One Way to Conduct a Replication Study: Beyond Statistical Significance” Anderson and Maxwell propose additional “replication goals” that should be considered in the planning of a study. We recommend this paper if you are interested in learning about a broader perspective on replication within the behavioral sciences.Read More
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