Patterns of intra-cluster correlation from primary care research to inform study design and analysis

被引:427
作者
Adams, G
Gulliford, MC
Ukoumunne, OC
Eldridge, S
Chinn, S
Campbell, MJ
机构
[1] Kings Coll London, Dept Publ Hlth Sci, London SE1 3QD, England
[2] Queen Marys Sch Med, Dept Primary Care, London, England
[3] Univ Sheffield, Inst Gen Practice & Primary Care, ScHARR, Sheffield S5 7AU, S Yorkshire, England
基金
英国医学研究理事会;
关键词
intraclass correlation; design effect; general practice; primary care; cluster randomization; cluster sampling;
D O I
10.1016/j.jclinepi.2003.12.013
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Objective: To provide information concerning the magnitude of the intraclass correlation coefficient (ICC) for cluster-based studies set in primary care. Study Design and Setting: Reanalysis of data from 31 cluster-based studies in primary care to estimate intraclass correlation coefficients from random effects models using maximum likelihood estimation. Results: ICCs were estimated for 1,039 variables. The median ICC was 0.010 (interquartile range [IQR] 0 to 0.032, range 0 to 0.840). After adjusting for individual- and cluster-level characteristics, the median ICC was 0.005 (IQR 0 to 0.021). A given measure showed widely varying ICC estimates in different datasets. In six datasets, the ICCs for SF-36 physical functioning scale ranged from 0.001 to 0.055 and for SF-36 general health from 0 to 0.072. In four datasets, the ICC for systolic blood pressure ranged from 0 to 0.052 and for diastolic blood pressure from 0 to 0.108. Conclusion: The precise magnitude of between-cluster variation for a given measure can rarely be estimated in advance. Studies should be designed with reference to the overall distribution of ICCs and with attention to features that increase efficiency. (C) 2004 Elsevier Inc. All rights reserved.
引用
收藏
页码:785 / 794
页数:10
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