Clinical Oral Investigations

, Volume 20, Issue 6, pp 1143–1149 | Cite as

Accounting for measurement reliability to improve the quality of inference in dental microhardness research: a worked example

Original Article

Abstract

Objectives

Dental microhardness experiments are influenced by unobserved factors related to the varying tooth characteristics that affect measurement reproducibility. This paper explores the appropriate analytical tools for modeling different sources of unobserved variability to reduce the biases encountered and increase the validity of microhardness studies.

Materials and methods

The enamel microhardness of human third molars was measured by Vickers diamond. The effects of five bleaching agents—10, 16, and 30 % carbamide peroxide, and 25 and 38 % hydrogen peroxide—were examined, as well as the effect of artificial saliva and amorphous calcium phosphate. To account for both between- and within-tooth heterogeneity in evaluating treatment effects, the statistical analysis was performed in the mixed-effects framework, which also included the appropriate weighting procedure to adjust for confounding. The results were compared to those of the standard ANOVA model usually applied.

Results

The weighted mixed-effects model produced the parameter estimates of different magnitude and significance than the standard ANOVA model. The results of the former model were more intuitive, with more precise estimates and better fit.

Conclusions

Confounding could seriously bias the study outcomes, highlighting the need for more robust statistical procedures in dental research that account for the measurement reliability. The presented framework is more flexible and informative than existing analytical techniques and may improve the quality of inference in dental research.

Clinical relevance

Reported results could be misleading if underlying heterogeneity of microhardness measurements is not taken into account. The confidence in treatment outcomes could be increased by applying the framework presented.

Keywords

Tooth bleaching Reproducibility of results Statistical models Weights and measures Treatment outcome Bias 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Institute for TourismZagrebCroatia
  2. 2.Department of Endodontics and Restorative Dentistry, School of Dental MedicineUniversity of ZagrebZagrebCroatia

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