Generalized Linear Mixed Models Part 3 of 5

>> YOUR LINK HERE: ___ http://youtube.com/watch?v=PjVTWHgs5OY

In this JMP Academic Webinar, we cover Generalized Linear Mixed Models in five parts. This is the third part of the series, covering where to find the JMP Add-In, how to install a JMP Add-In, and where to find more examples of using this JMP Add-In. • 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

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