What SAS and R software users need to know about GLMMs: an example-driven discussion

June 14, 2024, 9:00am
NORA M. BELLO, USDA Agricultural Research Service, Northeast Area, Beltsville, MD
WALTER STROUP, Dept. of Statistics, University of Nebraska, Lincoln, NE
RAÚL MACCHIAVELLI, College of Agricultural Sciences, University of Puerto Rico, Mayagüez, PR
BRUCE CRAIG, Dept. of Statistics, Purdue University, West Lafayette, IN
MARINA PTUKHINA, Dept. of Statistics, Whitman College, Walla Walla, WA
JULIE COUTON, Loop Returns

This group discussion will target conceptual and methodological best practices that users of generalized linear mixed models (GLMM) should know and address appropriately, regardless of choice of software platform. Using an example driven approach, we further describe software implementation of GLMMs in SAS and R. We present differential capabilities of these software platforms to address specific GLMM issues (to the best of our abilities). Last, we invite contributions from R-literate readers.

What SAS and R software users need to know about GLMMs: an example-driven discussion

Nora M. Bello

USDA Agricultural Research Service

Walter Stroup

Raúl Macchiavelli

University of Puerto Rico

Bruce Craig

Purdue University