Estimation of design effects in cluster surveys

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Cluster sampling can produce estimates of disease prevalence that are more variable than those from simple random sampling. This variance inflation or "design effect" depends on the prevalence of disease, the cluster sizes, and the magnitude of disease association within clusters. Design effects from prior surveys may not be appropriate for a planned survey if these components differ. We estimated within-cluster associations using pairwise odds ratios, which are more portable than design effects because they do not depend on the cluster sizes. Within-village pairwise odds ratios and design effects were estimated for fever and cough from four studies in Africa and Asia. Odds ratios ranged from 1.04 to 1.34 and 1.03 to 1.24, respectively. Design effects ranged from 2.35 to 6.80 for fever and 1.99 to 7.39 for cough. The design effect was more affected by cluster size and odds ratio than by variation in cluster size for a given sample size.

Original languageEnglish (US)
Pages (from-to)295-301
Number of pages7
JournalAnnals of epidemiology
Volume4
Issue number4
DOIs
StatePublished - Jul 1994

Keywords

  • Design effect
  • clustering
  • cough
  • fever
  • sample size

ASJC Scopus subject areas

  • Epidemiology

Fingerprint

Dive into the research topics of 'Estimation of design effects in cluster surveys'. Together they form a unique fingerprint.

Cite this