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J Public Health Dent. 2011 Winter;71(1):71-8. doi: 10.1111/j.1752-7325.2010.00197.x.

Multiple imputation of dental caries data using a zero-inflated Poisson regression model.

Author information

1
School of Dentistry, The University of North Carolina at Chapel Hill, 27599-7450, USA. bhavna_pahel@unc.edu

Abstract

Excess zeros exhibited by dental caries data require special attention when multiple imputation is applied to such data.

OBJECTIVE:

The objective of this study was to demonstrate a simple technique using a zero-inflated Poisson (ZIP) regression model, to perform multiple imputation for missing caries data.

METHODS:

The technique is demonstrated using data (n = 24,403) from a medical office-based preventive dental program in North Carolina, where 27.2 percent of children (n = 6,637) were missing information on physician-identified count of carious teeth. We first estimate a ZIP regression model using the nonmissing caries data (n = 17,766). The coefficients from the ZIP model are then used to predict the missing caries data.

RESULTS:

This technique results in imputed caries counts that are similar to the non-missing caries data in their distribution, especially with respect to the excess zeros in the nonmissing caries data.

CONCLUSION:

This technique can be easily applied to impute missing dental caries data.

PMID:
20880027
PMCID:
PMC3377436
DOI:
10.1111/j.1752-7325.2010.00197.x
[Indexed for MEDLINE]
Free PMC Article

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