Cluster randomized clinical trials in orthodontics: design, analysis and reporting issues

被引:11
|
作者
Pandis, Nikolaos [1 ]
Walsh, Tanya [2 ]
Polychronopoulou, Argy [3 ]
Eliades, Theodore [4 ]
机构
[1] Univ Bern, Dept Orthodont & Dentofacial Orthoped, Sch Dent, Fac Med, CH-3012 Bern, Switzerland
[2] Univ Manchester, Sch Dent, Manchester M13 9PL, Lancs, England
[3] Univ Athens, Dept Community & Prevent Dent, Sch Dent, GR-10679 Athens, Greece
[4] Univ Zurich, Dept Orthodont & Paediat Dent, Ctr Dent Med, CH-8006 Zurich, Switzerland
关键词
STATISTICS NOTES; SAMPLE-SIZE; COEFFICIENT; STATEMENT; CARIES;
D O I
10.1093/ejo/cjs072
中图分类号
R78 [口腔科学];
学科分类号
1003 ;
摘要
Cluster randomized trials (CRTs) use as the unit of randomization clusters, which are usually defined as a collection of individuals sharing some common characteristics. Common examples of clusters include entire dental practices, hospitals, schools, school classes, villages, and towns. Additionally, several measurements (repeated measurements) taken on the same individual at different time points are also considered to be clusters. In dentistry, CRTs are applicable as patients may be treated as clusters containing several individual teeth. CRTs require certain methodological procedures during sample calculation, randomization, data analysis, and reporting, which are often ignored in dental research publications. In general, due to similarity of the observations within clusters, each individual within a cluster provides less information compared with an individual in a non-clustered trial. Therefore, clustered designs require larger sample sizes compared with non-clustered randomized designs, and special statistical analyses that account for the fact that observations within clusters are correlated. It is the purpose of this article to highlight with relevant examples the important methodological characteristics of cluster randomized designs as they may be applied in orthodontics and to explain the problems that may arise if clustered observations are erroneously treated and analysed as independent (non-clustered).
引用
收藏
页码:669 / 675
页数:7
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