Is clustering accounted for in studies published in periodontology and oral implantology specialty journals?

Author:

Lempesi Evangelia1,Pandis Nikolaos2,Faggion Clovis3,Seehra Jadbinder4ORCID

Affiliation:

1. Department of Orthodontics and Dentofacial Orthopedics Hellenic Air Force General Hospital Athens Greece

2. Department of Orthodontics and Dentofacial Orthopedics, School of Dentistry University of Bern Bern Switzerland

3. Department of Periodontology and Operative Dentistry, Faculty of Dentistry University Hospital Münster Münster Germany

4. Centre for Craniofacial Development & Regeneration, Faculty of Dentistry Oral & Craniofacial Sciences, King's College London London United Kingdom

Abstract

AbstractBackgroundClustering effects can be encountered in periodontology and implant dentistry research. The aim of this study was to identify studies with clustering effects published in periodontology and oral implantology specialty journals and to assess the frequency by which clustered designs are correctly accounted for in the statistical analysis.MethodsTen periodontology and oral implantology journals were searched to identify studies with clustering effects published between January 1, 2019 and July 31, 2021. Descriptive statistics and frequency distributions were calculated. Associations between the correct statistical handling of clustering effects and study characteristics were explored.ResultsA total of 695 studies were included of which 45.0% correctly accounted for clustering effects in the statistical analysis. Certain journals (p < 0.01) and animal studies (p < 0.01) had lower odds of correctly accounting for clustering effects in the statistical analysis, whereas per unit increase in impact factor (p < 0.001), involvement of statistician (p < 0.001) and when the study design included either repeated measures only (p < 0.01) or both clustering and repeated measures (p < 0.001) had higher odds. The most commonly used tests were the mixed models or generalized estimating equations (64.2%).ConclusionsGreater awareness of the importance of accounting for clustering effects is required to prevent incorrect inferences being drawn. Incorrect inferences are related to lack of data independence and the artificial inflation of the sample size which can result in statistically significant results which are not genuine. This issue can be further exaggerated in combination with publication bias.

Publisher

Wiley

Subject

Periodontics,General Medicine

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