Components of Variance and Intraclass Correlations for the Design of Community-based Surveys and Intervention Studies: Data from the Health Survey for England 1994

The authors estimated components of variance and intraclass correlation coefficients (ICCs) to aid in the design of complex surveys and community intervention studies by analyzing data from the Health Survey for England 1994. This cross-sectional survey of English adults included data on a range of...

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Bibliographic Details
Published in:American journal of epidemiology 1999-05, Vol.149 (9), p.876-883
Main Authors: Gulliford, Martin C., Ukoumunne, Obioha C., Chinn, Susan
Format: Article
Language:English
Subjects:
Biological and medical sciences
Cluster Analysis
Cross-Sectional Studies
data collection
Data Interpretation, Statistical
England - epidemiology
epidemiologic methods
Epidemiologic Studies
Epidemiology
General aspects
Health Status
Health Surveys
Humans
intraclass correlation
Life Style
Medical sciences
Methodology
Public health. Hygiene
Public health. Hygiene-occupational medicine
random allocation
Research Design
Risk Factors
sampling studies
statistics
variance
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Summary:The authors estimated components of variance and intraclass correlation coefficients (ICCs) to aid in the design of complex surveys and community intervention studies by analyzing data from the Health Survey for England 1994. This cross-sectional survey of English adults included data on a range of lifestyle risk factors and health outcomes. For the survey, households were sampled in 720 postal code sectors nested within 177 district health authorities and 14 regional health authorities. Study subjects were adults aged 16 years or more. ICCs and components of variance were estimated from a nested random-effects analysis of variance. Results are presented at the district health authority, postal code sector, and household levels. Between-cluster variation was evident at each level of clustering. In these data, ICCs were inversely related to cluster size, but design effects could be substantial when the cluster size was large. Most ICCs were below 0.01 at the district health authority level, and they were mostly below 0.05 at the postal code sector level. At the household level, many ICCs were in the range of 0.0–0.3. These data may provide useful information for the design of epidemiologic studies in which the units sampled or allocated range in size from households to large administrative areas. Am J Epidemiol 1999;149:876–83.
ISSN:0002-9262
1476-6256
DOI:10.1093/oxfordjournals.aje.a009904