Publication date: 06/21/2023
Generalized Linear Models
Fit Models for Nonnormal Response Distributions
The Generalized Linear Model personality of the Fit Model platform enables you to fit generalized linear models for responses with binomial, normal, Poisson, or exponential distributions. The platform provides reports similar to those that are provided for traditional linear models. The platform also accommodates separation in logistic regression models using the Firth correction.
Generalized linear models provide a unified way to fit responses that do not fit the usual requirements of traditional linear models. For example, frequency counts are often characterized as having a Poisson distribution and fit using a generalized linear model.
Figure 13.1 Example of a Generalized Linear Model Fit
Contents
Overview of the Generalized Linear Model Personality
Example of a Generalized Linear Model
Launch the Generalized Linear Model Personality
Generalized Linear Model Fit Report
Whole Model Test
Generalized Linear Model Fit Report Options
Additional Examples of the Generalized Linear Models Personality
Example of Using Contrasts in a Generalized Linear Model
Example of Poisson Regression with an Offset
Example of Normal Regression with a Log Link
Statistical Details for the Generalized Linear Model Personality
Statistical Details for Generalized Linear Model Construction
Statistical Details for Model Selection and Deviance
Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).