Poisson Regression

Summary of Model

The model summary table contains statistics that you can use to select a model. The table includes three statistics:

· Deviance R-Sq is typically thought of as the proportion of the deviance in the data that the model explains. The larger the deviance R $image\squared.gif$ , the better the model fits the data.

· Deviance R-Sq(adj) is a modified deviance R $image\squared.gif$ that is adjusted for the number of terms in the model. Use the adjusted statistic to compare models with different numbers of predictors.

· Akaike Information Criterion (AIC) also measures model fit. The smaller the AIC, the better the model fits the data.

Example Output

Model Summary

Deviance Deviance

R-Sq R-Sq(adj) AIC

64.20% 60.80% 253.29

Interpretation

For the resin defect data, deviance R2 is 64.20%, adjusted deviance R2 is 60.80% and AIC is 253.29. Higher values of the R2 statistics or a lower value of AIC for another model suggests that a different set of predictors does a better job.