Best Practices for GLMM Implementation: Group Updates and Planning

June 11, 2026, 1:30pm
Nora M. Bello, United States Department of Agriculture – Agricultural Research Service, Beltsville, MD
Bruce A. Craig, Department of Statistics, Purdue University
Xin Dai, Animal, Dairy & Veterinary Sciences, Utah State University
Philip Dixon, Department of Statistics, Iowa State University
Susan L. Durham, Department of Watershed Sciences and Ecology Center, Utah State University
Conor G. Fair, College of Agricultural and Environmental Sciences, University of Georgia
Réka Howard, Department of Statistics, University of Nebraska-Lincoln
Clark Kogan, Department of Pharmaceutical Sciences, Washington State University
Josefina Lacasa, Department of Statistics, Kansas State University
Raúl E. Macchiavelli, College of Agricultural Sciences, University of Puerto Rico
Daniel G. Palmer, StatsCraft, Spokane, WA
Julia Piaskowski, Director of Statistical Programs, College of Agricultural and Life Sciences, University of Idaho
Quentin D. Read, United States Department of Agriculture – Agricultural Research Service, Beltsville, MD
Walter W. Stroup, Department of Statistics, University of Nebraska-Lincoln

Our ongoing project initiated in 2024 and investigates best practices for the application of Generalized Linear Mixed Models (GLMMs), including topics in statistical modeling and software implementation. As we transition into the project’s next phase, this meeting will serve as a working session to review our progress and plan our future steps. We will prioritize discussions around our publication roadmap and the immediate actionable steps required to successfully deliver our findings.