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.