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Efficiency Issues Among Statistical Methods for Demonstrating Efficacy of Caries Prevention

¹ Department of Dental Public Health Sciences and
² Department of Biostatistics, University of Washington, Box 357475, Seattle, WA 98195-7475;

^* corresponding author, llman{at}u.washington.edu

Although repeated tooth-surface-specific information is commonly collected during a longitudinal caries clinical trial, traditional methods often make limited use of the repeated measures. Newer methods of analysis, such as methods based on time-to-event and methods for longitudinal or clustered data, have the potential to increase the efficiency of the statistical analysis. We compare a range of analytical methods from the traditional analysis based only on the number of caries onsets to newer methods that incorporate time at risk and surface-specific information, such as Poisson regression methods for clustered data, with respect to the efficiency of treatment comparisons. Under most circumstances, the greatest gain in efficiency associated with time-to-event methods will be due to the ability of subjects to contribute caries onsets to the analysis until they are lost from the study. Incorporating the number of surfaces at risk, the surface time at risk, and surface-specific characteristics will typically produce only a modest gain in efficiency.

KEY WORDS: Poisson regression • survival analysis • correlated data

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				J.W. Stamm The Classic Caries Clinical Trial: Constraints and Opportunities J. Dent. Res., July 1, 2004; 83(suppl_1): C6 - C14. [Full Text] [PDF]