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

Clicks: 1
ID: 302147
1999
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #235 of 305 articles by views in american journal of epidemiology

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 305 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
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.
Reference Key
openalex_W1977185679 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Martin Gulliford, Obioha C. Ukoumunne, S Chinn
Journal american journal of epidemiology
Year 1999
DOI
10.1093/oxfordjournals.aje.a009904
URL
https://academic.oup.com/aje/article-pdf/149/9/876/264847/149-9-876.pdf
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.