Multiple imputation of dental caries data using a zero-inflated Poisson regression model
Article first published online: 28 SEP 2010
© 2010 American Association of Public Health Dentistry
Journal of Public Health Dentistry
Volume 71, Issue 1, pages 71–78, Winter 2011
How to Cite
Pahel, B. T., Preisser, J. S., Stearns, S. C. and Rozier, R. G. (2011), Multiple imputation of dental caries data using a zero-inflated Poisson regression model. Journal of Public Health Dentistry, 71: 71–78. doi: 10.1111/j.1752-7325.2010.00197.x
- Issue published online: 18 MAR 2011
- Article first published online: 28 SEP 2010
- Received: 2/10/2009; accepted: 8/6/2010.
- dental caries;
- zero inflated Poisson regression;
- mixture model
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 nonmissing 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.