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Related Experiment Videos

Using design effects from previous cluster surveys to guide sample size calculation in emergency settings.

Reinhard Kaiser1, Bradley A Woodruff, Oleg Bilukha

  • 1European Centre for Disease Prevention and Control, Stockholm, Sweden. reinhard.kaiser@ecdc.eu.int

Disasters
|May 13, 2006
PubMed
Summary

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Estimating design effects is key for efficient cluster surveys. A design effect of 1.5 for child malnutrition and <=2 for crude mortality is often sufficient, improving sample size calculations.

Area of Science:

  • Public Health and Epidemiology
  • Biostatistics
  • Survey Methodology

Background:

  • Accurate sample size calculation for cluster surveys relies on a precise estimation of the design effect (DEFF).
  • Cluster surveys are frequently employed in emergency settings to assess health and nutrition outcomes.

Purpose of the Study:

  • To review design effects for various nutrition and health indicators from population-based cluster surveys in emergency contexts.
  • To inform more efficient sample size calculations by reassessing the impact of DEFF on precision.

Main Methods:

  • Review of design effects for seven nutrition and health outcomes across nine population-based cluster surveys.
  • Analysis of mortality data from specific emergency settings (Kosovo, Badghis, Afghanistan) to assess the impact of sample size variations.

Related Experiment Videos

  • Reassessment of the relationship between the number of clusters, sample size, and precision of mortality estimates.

    • Main Results:

    • Most design effects for child nutrition outcomes were below two.
    • Approximately half of the design effects for crude mortality were also below two.
    • Increasing sample size within a fixed number of clusters had a minimal impact on the precision of mortality estimates.

    Conclusions:

    • Assuming a design effect of 1.5 for acute malnutrition in children and two or less for crude mortality can lead to more efficient sample size determination in most surveys.
    • Increasing sample size without augmenting the number of clusters in cluster surveys may not significantly enhance precision.
    • These findings support refined DEFF assumptions for optimizing survey design in humanitarian and health research.