http://m.statisticalhorizons.com/?url=http%3A%2F%2Fstatisticalhorizons.com%2Fzero-inflated-models

*"In all data sets that I've examined, the negative binomial model fits much better than a ZIP model, as evaluated by AIC or BIC statistics. And it's a much simpler model to estimate and interpret. So if the choice is between ZIP and negative binomial, I'd almost always choose the latter."*

"But what about the zero-inflated negative binomial (ZINB) model? It's certainly possible that a ZINB model could fit better than a conventional negative binomial model regression model. But the latter is a special case of the former, so it's easy to do a likelihood ratio test to compare them (by taking twice the positive difference in the log-likelihoods). In my experience, the difference in fit is usually trivial..."

"So next time you're thinking about fitting a zero-inflated regression model, first consider whether a conventional negative binomial model might be good enough. Having a lot of zeros doesn't necessarily mean that you need a zero-inflated model."

"But what about the zero-inflated negative binomial (ZINB) model? It's certainly possible that a ZINB model could fit better than a conventional negative binomial model regression model. But the latter is a special case of the former, so it's easy to do a likelihood ratio test to compare them (by taking twice the positive difference in the log-likelihoods). In my experience, the difference in fit is usually trivial..."

"So next time you're thinking about fitting a zero-inflated regression model, first consider whether a conventional negative binomial model might be good enough. Having a lot of zeros doesn't necessarily mean that you need a zero-inflated model."

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