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Related Experiment Videos

Determination of sample sizes for epidemiological surveys using cluster sampling technique.

L Jeyaseelan1, P S Rao

  • 1Department of Biostatistics, Christian Medical College, Vellore.

Indian Journal of Leprosy
|January 1, 1989
PubMed
Summary

Cluster sampling offers a cost-effective method for epidemiological surveys, though it requires larger sample sizes due to intra-class correlation. This paper discusses its strengths and weaknesses, particularly for leprosy control programs.

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Public Health

Background:

  • Cluster sampling is a cost-effective technique for epidemiological surveys.
  • It often requires larger sample sizes than individual-based sampling due to intra-class correlation.
  • The intra-class correlation coefficient is frequently unknown, necessitating estimations or assumptions.

Purpose of the Study:

  • To present the strengths and weaknesses of cluster sampling in epidemiological surveys.
  • To discuss the application of cluster sampling in leprosy control programs.
  • To propose a multistage cluster sampling model for district-level program evaluation.

Main Methods:

  • Review of cluster sampling principles and comparison with other sampling plans.
  • Discussion of intra-class correlation and its impact on sample size.

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  • Proposal of a multistage cluster sampling model for program evaluation.

    • Main Results:

    • Cluster sampling provides convenience and cost-effectiveness but increases sample size requirements.
    • Strengths and weaknesses are detailed with specific reference to leprosy control.
    • A multistage cluster sampling model is suggested for evaluating district-level programs.

    Conclusions:

    • Cluster sampling is a valuable tool in epidemiological surveys, especially for resource-limited settings like leprosy control.
    • Careful consideration of intra-class correlation is crucial for accurate sample size determination.
    • The proposed multistage model can effectively evaluate district-level health programs.