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Evaluating the Effects of Different Polishing Methods on Color Stability of Dental Restorations in Pediatric Dentistry

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Does published orthodontic research account for clustering effects during statistical data analysis?

Despina Koletsi¹, Nikolaos Pandis, Argy Polychronopoulou

¹Department of Orthodontics, School of Dentistry, University of Athens, Greece.

European Journal of Orthodontics

|October 22, 2011

Summary

Orthodontic studies often have clustered data, but only 25% of them properly account for these effects in their statistical analysis. This highlights a gap in applying appropriate methods for correlated observations in orthodontic research.

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Area of Science:

Orthodontics
Biostatistics
Clinical Research Design

Background:

Orthodontic research frequently involves clustered data, such as repeated measures within patients or multi-center studies.
Clustered designs necessitate specialized statistical analyses to address the correlation between observations within clusters.
Ignoring clustering effects can lead to inaccurate statistical inferences and potentially flawed conclusions.

Purpose of the Study:

To evaluate the extent to which clustering effects are addressed in study design and data analysis.
To assess statistical practices in major orthodontic journals regarding clustered data.
To identify factors associated with the appropriate handling of clustering effects.

Main Methods:

A hand search of the 24 most recent issues (backdated from December 2010) of three leading orthodontic journals: AJODO, AO, and EJO.
Identification of articles with inherent clustering effects and assessment of whether authors accounted for these effects.
Collection of data on study characteristics, including statistician involvement, study setting, author count, and geographical origin.

Main Results:

Out of 1062 assessed articles, 250 (23.5%) exhibited clustering effects in their design.
Only 63 (25.2%) of the studies with clustering effects indicated that these effects were accounted for in the analysis.
Studies published in Angle Orthodontist (AO) showed significantly higher odds of accounting for clustering effects compared to AJODO (OR=2.17, P=0.03).

Conclusions:

A significant proportion of orthodontic research with clustered data fails to adequately address these effects in statistical analysis.
There is a need for improved awareness and application of statistical methods for clustered data in orthodontic publications.
Journal-specific differences exist in the reporting and handling of clustering effects, suggesting a need for consistent editorial policies.