# The analysis of zero-inflated count data:

beyond zero-inflated Poisson regression

This
webpage contains the supplementary material (data, R code & extra
examples) for the paper

"The analysis of zero-inflated count
data: beyond zero-inflated Poisson regression" (under revision
for the British Journal of Mathematical and Statistical Psychology).

## Example:
Modelling Unwanted Pursuit Behaviour

In this example, we use zero-inflated and
hurdle Poisson models to investigate the impact of 'education
level' and 'level of anxious attachment' on the number of unwanted
pursuit behaviour
(UPB) perpetrations in the context of couple separation trajectories.
The data are part of the Interdisciplinary Project for the
Optimization of Separation trajectories conducted in Flanders (IPOS;
www.scheidingsonderzoek.be).

### Data

Couple.txt

### R-code

__A__nalysis
UPB.R

## Artificial
example 1

This example illustrates a
common misinterpretation in the zero-inflated Poisson models
concerning the effects of predictors on the excess zeroes. It is
shown how hurdle models can make interpretation more straightforward
by directly modelling the effects on all zero counts
instead on the excess zero counts.

### Example

Artificial
example 1.pdf

### R-code

Artificial
example 1.R

## Artificial
example 2

This example illustrates the need
for caution when interpreting interaction effects in the
zero-inflated Poisson models and the hurdle models.

### Example

Artificial
example 2.pdf

### R-code

Artificial
example 2.R