Generalized Linear Mixed Models: Part 1 (of 5)

In this JMP Academic Webinar, we cover Generalized Linear Mixed Models in five parts. This is the first part of the series, covering mixed models, interaction plots, and LSMeans. GLMM Part 1: Intro, Experiment, and lots about Mixed Models (24:09) Welcome, and reminder of LM, GLM, MM, and GLMM: 0:00 Agenda: 2:32 Review of random effects and mixed models: 3:37 Key difference between a fixed effect and a random effect 7:06 Summary of Experiment: 9:22 Showing the personalities in Fit Model 12:12 Using SLS and Mixed personalities and seeing the same model but some different output options14:02 Exploring the interaction and the overlay plot for the mixed model 17:54 Understanding LSMeans 19:19 GLMM Part 2: More about GLMMs (7:04) Count data (a Poisson distribution) 0:00 Details about and examples of GLMMs 2:35 Model + Distribution + Link 4:40 Details about REPL estimation GLMM Part 3: Download and install the Add-In and find more examples! (4:18) Webpage to download add-in and find more examples 0:00 Downloading and installing the add-in 1:54 Credit to the Add-In author, Meichen Dong 3:32 GLMM Part 4: Count example with Poisson distribution and LOTS of Graphing tips (27:40) Setting up the Poisson Mixed Model 0:00 Back-transforming Estimates and CIs 2:52 Graph Builder for the Interaction Plot (with lots of JMP tips!!) 10:05 Saving Figures and Output and Data 17:17 Overdispersion 18:20 Back-transforming pairwise comparisons 25:38 Where to find more examples and ask questions 27:08 GLMM Part 5: Proportion example with Binomial Distribution (9:17) Introducing the Binomial Scenario 0:00 Fitting the binomial GLMM 1:39 Back-transforming Estimates and CIs 4:00 Interaction Plot 6:46 Where to find more examples and ask questions 8:39