The analysis of zero-inflated count data: beyond zero-inflated poisson regression
- Author
- Tom Loeys (UGent) , Beatrijs Moerkerke (UGent) , Olivia De Smet (UGent) and Ann Buysse (UGent)
- Organization
- Abstract
- Infrequent count data in psychological research are commonly modelled using zeroinflated Poisson regression. This model can be viewed as a latent mixture of an “alwayszero” component and a Poisson component. Hurdle models are an alternative class of two-component models that are seldom used in psychological research, but clearly separate the zero counts and the non-zero counts by using a left-truncated count model for the latter. In this tutorial we revisit both classes of models, and discuss model comparisons and the interpretation of their parameters. As illustrated with an example from relational psychology, both types of models can easily be fitted using the R-package pscl.
- Keywords
- hurdle model, zero-inflated model, Count regression
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-2002243
- MLA
- Loeys, Tom, et al. “The Analysis of Zero-Inflated Count Data: Beyond Zero-Inflated Poisson Regression.” BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY, vol. 65, no. 1, 2012, pp. 163–80, doi:10.1111/j.2044-8317.2011.02031.x.
- APA
- Loeys, T., Moerkerke, B., De Smet, O., & Buysse, A. (2012). The analysis of zero-inflated count data: beyond zero-inflated poisson regression. BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY, 65(1), 163–180. https://doi.org/10.1111/j.2044-8317.2011.02031.x
- Chicago author-date
- Loeys, Tom, Beatrijs Moerkerke, Olivia De Smet, and Ann Buysse. 2012. “The Analysis of Zero-Inflated Count Data: Beyond Zero-Inflated Poisson Regression.” BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY 65 (1): 163–80. https://doi.org/10.1111/j.2044-8317.2011.02031.x.
- Chicago author-date (all authors)
- Loeys, Tom, Beatrijs Moerkerke, Olivia De Smet, and Ann Buysse. 2012. “The Analysis of Zero-Inflated Count Data: Beyond Zero-Inflated Poisson Regression.” BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY 65 (1): 163–180. doi:10.1111/j.2044-8317.2011.02031.x.
- Vancouver
- 1.Loeys T, Moerkerke B, De Smet O, Buysse A. The analysis of zero-inflated count data: beyond zero-inflated poisson regression. BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY. 2012;65(1):163–80.
- IEEE
- [1]T. Loeys, B. Moerkerke, O. De Smet, and A. Buysse, “The analysis of zero-inflated count data: beyond zero-inflated poisson regression,” BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY, vol. 65, no. 1, pp. 163–180, 2012.
@article{2002243,
abstract = {{Infrequent count data in psychological research are commonly modelled using zeroinflated Poisson regression. This model can be viewed as a latent mixture of an “alwayszero” component and a Poisson component. Hurdle models are an alternative class of two-component models that are seldom used in psychological research, but clearly separate the zero counts and the non-zero counts by using a left-truncated count model for the latter. In this tutorial we revisit both classes of models, and discuss model comparisons and the interpretation of their parameters. As illustrated with an example from relational psychology, both types of models can easily be fitted using the R-package pscl.}},
author = {{Loeys, Tom and Moerkerke, Beatrijs and De Smet, Olivia and Buysse, Ann}},
issn = {{0007-1102}},
journal = {{BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY}},
keywords = {{hurdle model,zero-inflated model,Count regression}},
language = {{eng}},
number = {{1}},
pages = {{163--180}},
title = {{The analysis of zero-inflated count data: beyond zero-inflated poisson regression}},
url = {{http://doi.org/10.1111/j.2044-8317.2011.02031.x}},
volume = {{65}},
year = {{2012}},
}
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