LAUSR

BACKGROUND Clustering 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. METHODS 10 Periodontology and oral Implantology journals were searched to identify studies with clustering effects published between 1st January 2019 and 31st July 2021. Descriptive statistics and frequency distributions were calculated. Associations between the correct statistical handling of clustering effects and study characteristics were explored. RESULTS 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 GEE (64.2%). CONCLUSIONS Greater 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. This article is protected by copyright. All rights reserved.