Two-part regression models for longitudinal zero-inflated count data
✍ Scribed by Marco Alfò; Antonello Maruotti
- Publisher
- John Wiley and Sons
- Year
- 2010
- Tongue
- French
- Weight
- 162 KB
- Volume
- 38
- Category
- Article
- ISSN
- 0319-5724
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## Abstract In many biometrical applications, the count data encountered often contain extra zeros relative to the Poisson distribution. Zero‐inflated Poisson regression models are useful for analyzing such data, but parameter estimates may be seriously biased if the nonzero observations are over‐d
## Abstract Two‐part regression models are frequently used to analyze longitudinal count data with excess zeros, where the same set of subjects is repeatedly observed over time. In this context, several sources of heterogeneity may arise at individual level that affect the observed process. Further