Assistant Professor
Department of Biostatistics
School of Public Health and Health Professions
University at Buffalo
South Campus
University at Buffalo
Correlated data arise frequently in scientific fields. This may be due to grouping of subjects or repeated measurements on each subject over time. Mixed model analysis provides a general, flexible approach in these situations. It allows a wide variety of correlation patterns to be explicitly modeled. In this workshop, we will introduce some mixed models such as the random intercept model, random slope model and the general framework of the linear mixed-effects model.
ACCREDITATION: The University at Buffalo Jacobs School of Medicine and Biomedical Sciences is accredited by the ACCME to provide continuing medical education for physicians.
CERTIFICATION: The University at Buffalo Jacobs School of Medicine and Biomedical Sciences designates this live activity for a maximum of 2.0 AMA PRA Category 1 Credit(s)TM. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
CREDIT: This program is supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award number UL1TR001412.