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.
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.
Authors: K Lakshminarayan; C Borbas; B McLaughlin; N E Morris; G Vazquez; R V Luepker; D C Anderson Journal: Neurology Date: 2010-05-18 Impact factor: 9.910
Authors: Marijke Boorsma; Dinnus H M Frijters; Dirk L Knol; Miel E Ribbe; Giel Nijpels; Hein P J van Hout Journal: CMAJ Date: 2011-06-27 Impact factor: 8.262
Authors: Catherine M Sackley; Maayken E van den Berg; Karen Lett; Smitaa Patel; Kristen Hollands; Christine C Wright; Thomas J Hoppitt Journal: BMJ Date: 2009-09-01