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Cited by 377

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The Zero-Inflated Poisson Model and the Decayed, Missing and Filled Teeth Index in Dental Epidemiology

Böhning, Dankmar, Dietz, E., Schlattmann, P., Mendonça, L., Kirchner, U.·1999·Journal of the Royal Statistical Society Series A: Statistics in Society

Abstract

Summary: For frequency counts, the situation of extra zeros often arises in biomedical applications. This is demonstrated with count data from a dental epidemiological study in Belo Horizonte (the Belo Horizonte caries prevention study) which evaluated various programmes for reducing caries. Extra zeros, however, violate the variance–mean relationship of the Poisson error structure. This extra-Poisson variation can easily be explained by a special mixture model, the zero-inflated Poisson (ZIP) model. On the basis of the ZIP model, a graphical device is presented which not only summarizes the mixing distribution but also provides visual information about the overall mean. This device can be exploited to evaluate and compare various groups. Ways are discussed to include covariates and to develop an extension of the conventional Poisson regression. Finally, a method to evaluate intervention effects on the basis of the ZIP regression model is described and applied to the data of the Belo Horizonte caries prevention study.

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Metadata

Authors
Böhning, D., Dietz, E., Schlattmann, P., Mendonça, L., & Kirchner, U.
Venue
Journal of the Royal Statistical Society Series A: Statistics in Society
Published
1999-03-01
Volume
162
Issue
2
Pages
195-209
ISSN
  • 0964-1998 (ISSN-L)
  • 1467-985X
OpenAlex
W2150462512
Cited by
377
References
1
FWCI
5.71
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Zero-Inflated Poisson Model and the Decayed, Missing and Filled Teeth Index in Dental Epidemiology. https://app.cochat.ai/papers/10.1111/1467-985x.00130
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Böhning, D., Dietz, E., Schlattmann, P., Mendonça, L., & Kirchner, U. (1999). The Zero-Inflated Poisson Model and the Decayed, Missing and Filled Teeth Index in Dental Epidemiology. Journal of the Royal Statistical Society Series A: Statistics in Society. https://doi.org/10.1111/1467-985x.00130

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