Generalized Linear Mixed Models
Fit a Variety of Mixed Models to Nonnormal Response Data
The Generalized Linear Mixed Model personality of the Fit Model platform is available only in JMP Pro.
The Generalized Linear Mixed Model personality fits models that have a non-Gaussian response variable and random design effects such as blocking. Using the generalized linear model framework enables you to accurately estimate standard errors for the parameters. Using the mixed model framework enables you to accurately represent random effects. The GLMM framework combines these two approaches and gives you the power to test hypotheses and have accurate estimation. The Generalized Linear Mixed Model personality can fit models for continuous, count, and binomial response variables.
Figure 9.1 Conditional Model Profiler for a Generalized Linear Mixed Model
