Education 231C

Applied Categorical & Nonnormal Data Analysis

Zero-Inflated count Models

In many instances the number of zeros in a count model can be increased because some of the zeros are generated by a different process than the remaining counts. Using data on doctoral publications, as an example, while many scientists are actively involved in research and publication some have jobs in which research and publishing is not required or even possible.

We will illustrate zero inflated count models using Long's data on doctoral publications.

Zero-inflated Poisson

The vuong option is included to obtain a test of zip versus poisson, which in this case favors zip.

Zero-inflated Negative Binomial

We have included the vuong and zip options. zip requests that a likelihood-ratio test comparing zinb with zip be included. The results indicate that zinb is the better choice. vuong was used to obtain a test of the zinb versus nbreg models. In general, Vuong test that are significantly positive support the zero-inflated models, while those that are significantly negative favor nonzero-inflated models. The Vuong test above supports the use of a zero-inflated approach.

Let's try again and see if we can improve our model by removing some non-significant variables.

Categorical Data Analysis Course

Phil Ender