Planning a cluster randomized trial with unequal cluster sizes: Practical issues involving continuous outcomes

被引：49
作者：
Guittet L. [1 ,2 ]
Ravaud P. [1 ,2 ]
Giraudeau B. [3 ,4 ]
机构：
[1] Département d'Epidémiologie, Biostatistique et Recherche Clinique, Université Xavier Bichat, Paris
[2] INSERM U 738, Université Paris 7, Paris
[3] INSERM CIC 202, Université François Rabelais de Tours, CHRU de Tours
[4] INSERM U 717, Université Paris 7, Paris
来源：
BMC Medical Research Methodology | / 6卷 / 1期
关键词：
Intraclass Correlation Coefficient; Cluster Size; Sample Size Calculation; Variance Inflation Factor; Planning Stage;
D O I：
10.1186/1471-2288-6-17
中图分类号：
学科分类号：
摘要：
Background: Cluster randomization design is increasingly used for the evaluation of health-care, screeening or educational interventions. At the planning stage, sample size calculations usually consider an average cluster size without taking into account any potential imbalance in cluster size. However, there may exist high discrepancies in cluster sizes. Methods: We performed simulations to study the impact of an imbalance in cluster size on power. We determined by simulations to which extent four methods proposed to adapt the sample size calculations to a pre-specified imbalance in cluster size could lead to adequately powered trials. Results: We showed that an imbalance in cluster size can be of high influence on the power in the case of severe imbalance, particularly if the number of clusters is low and/or the intraclass correlation coefficient is high. In the case of a severe imbalance, our simulations confirmed that the minimum variance weights correction of the variation inflaction factor (VIF) used in the sample size calculations has the best properties. Conclusion: Publication of cluster sizes is important to assess the real power of the trial which was conducted and to help designing future trials. We derived an adaptation of the VIF from the minimum variance weights correction to be used in case the imbalance can be a priori formulated such as a proportion (γ) of clusters actually recruit a proportion (τ) of subjects to be included (γ ≤ τ)". © 2006 Guittet et al; licensee BioMed Central Ltd."
引用
收藏
相关论文
共 25 条
  • [21] Lake S., Kammann E., Klar N., Betensky R., Sample size re-estimation in cluster randomization trials, Stat Med, 21, pp. 1337-1350, (2002)
  • [22] Edwards S.J., Braunholtz D.A., Lilford R.J., Stevens A.J., Ethical issues in the design and conduct of cluster randomised controlled trials, BMJ, 318, pp. 1407-1409, (1999)
  • [23] Haidich A.B., Ioannidis J.P.A., The Gini coefficient as a measure for understanding accrual inequalities in multicenter clinical trials, J Clin Epidemiol, 57, pp. 341-348, (2004)
  • [24] Puffer S., Torgerson D., Watson J., Evidence for risk of bias in cluster randomised trials: Review of recent trials published in three medical journals, BMJ, 327, pp. 785-789, (2003)
  • [25] Campbell M.K., Elbourne D.R., Altman D.G., CONSORT statement: Extension to cluster randomised trials, BMJ, 328, pp. 702-708, (2004)
123