Header

UZH-Logo

Maintenance Infos

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


Pandis, Nikolaos; Walsh, Tanya; Polychronopoulou, Argy; Eliades, Theodore (2013). Cluster randomized clinical trials in orthodontics: design, analysis and reporting issues. European Journal of Orthodontics, 35(5):669-675.

Abstract

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).

Abstract

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).

Statistics

Citations

4 citations in Web of Science®
3 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

2 downloads since deposited on 11 Jan 2013
0 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Center for Dental Medicine > Clinic for Orthodontics and Pediatric Dentistry
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2013
Deposited On:11 Jan 2013 09:46
Last Modified:07 Dec 2017 18:12
Publisher:Oxford University Press
ISSN:0141-5387
Publisher DOI:https://doi.org/10.1093/ejo/cjs072
PubMed ID:23041934

Download