Which is the best model for zero inflated data?

Which is the best model for zero inflated data?

Results from simulated and real data showed that the zero- altered or zero-inflated negative binomial model were preferred over others (e.g., ordinary least-squares regression with log-transformed outcome, Poisson model) when data have excessive zeros and over-dispersion.

When to use zero inflated Poisson regression in Stata?

Version info: Code for this page was tested in Stata 12. Zero-inflated poisson regression is used to model count data that has an excess of zero counts. Further, theory suggests that the excess zeros are generated by a separate process from the count values and that the excess zeros can be modeled independently.

Why are there excess zeros in the Stata data?

Some visitors do not fish, but there is no data on whether a person fished or not. Some visitors who did fish did not catch any fish so there are excess zeros in the data because of the people that did not fish. Let’s pursue Example 2 from above. The data set used in this example is from Stata. We have data on 250 groups that went to a park.

How is the inflate coefficient used in Stata 11?

The inflate coefficient for persons suggests that for each unit increase in person the log odds of an inflated zero decrease by .564. We can use the margins (introduced in Stata 11) to help understand our model.

Are there any problems with zinb zero inflated model?

Since zinb has both a count model and a logit model, each of the two models should have good predictors. The two models do not necessarily need to use the same predictors. Problems of perfect prediction, separation or partial separation can occur in the logistic part of the zero-inflated model.

Which is better Poisson or zero inflated binomial regression?

This suggests that our data is overdispersed and that a zero-inflated negative binomial model is more appropriate than a zero-inflated Poisson model. The Vuong test suggests that the zero-inflated negative binomial model is a significant improvement over a standard negative binomial model.

Which is better a Poisson model or a zero inflated model?

The Vuong test compares the zero-inflated model with an ordinary Poisson regression model. In this example, we can see that our test statistic is significant, indicating that the zero-inflated model is superior to the standard Poisson model.

Is the logit model predictor of excessive zeros?

The predictor person in the part of the logit model predicting excessive zeros is statistically significant. For these data, the expected change in log ( count ) for a one-unit increase in child is -1.515255 holding other variables constant.