December 1, 2016
Latent class analysis (LCA) is a widely used tool for identifying subgroups in a population. Many researchers have questions about how to conduct an LCA as responsibly and accurately as possible. In our latest podcast, John Dziak discusses important points to consider when conducting an LCA, like how to tell when an analysis is successful and how to make sure your model is properly identified. John is a Methodology Center research associate who studies LCA, and he is the lead developer of our LCA software, including PROC LCA. Note: this podcast is a companion piece to podcasts 15 and 16 with Stephanie Lanza and Bethany Bray. If you are new to LCA, you may want to start with Podcast 15.