In this workshop we introduces zero-inflated Poisson, zero-inflated negative binomial, and hurdle models for count data, which are two-part models used when more zeros are found in the data than expected with typical count distributions. We will discuss the formulations of the two parts of each model, the interpretation of model parameters, and how to run these models and analyze zero-inflated count data in R.

If you would like to run the R code for this workshop, please ensure that your version of R is up to date and install the packages used in the workshop by running the following code in R:

install.packages(c(“tidyverse”, “AER”, “pscl”, “MASS”, “performance”, “sandwich”, “sjPlot”, “lmtest”,”emmeans”), dependencies = TRUE)

You can download the seminar slides here and the R code for the workshop here.

If you are not familiar with Generalized linear models we suggest you take a look at our workshop on Introduction to Generalized Linear Regression Model in R

If you are new to R, watch this seminar.

And check this one: Introduction to Regression in R or this: Introduction to Linear Regression in R