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Patterns of intra-cluster correlation from primary care research to inform study design and analysis
Geoffrey Adams1, Martin C Gulliford, Obioha C Ukoumunne
1Department of Public Health Sciences, King's College London, Capital House, 42 Weston Street, London SE1 3QD, UK.
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.
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