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Related Experiment Videos

Variance estimation for complex surveys using replication techniques

K F Rust1, J N Rao

  • 1Westat, Inc., Rockville, MD 20850-3129, USA.

Statistical Methods in Medical Research
|September 1, 1996
PubMed
Summary

Specialized methods are crucial for analyzing survey data, accounting for sample design effects. Replication techniques like the jackknife, balanced repeated replication, and bootstrap offer robust approaches for variance estimation and inference in complex surveys.

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Area of Science:

  • Statistics
  • Survey Methodology

Background:

  • Survey data analysis necessitates specialized methods to address sample design impacts on estimators and test statistics.
  • Replication techniques provide a viable approach to manage these complexities in statistical analysis.

Purpose of the Study:

  • To discuss the application of replication techniques for estimating sampling variances.
  • To explain the use of these variance estimates for drawing inferences from survey data.
  • To outline examples of replication methods in analyzing large, complex surveys.

Main Methods:

  • Description of the jackknife technique.
  • Explanation of balanced repeated replication (balanced half-samples).
  • Overview of the bootstrap method.

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Main Results:

  • Summarization of the properties of jackknife, balanced repeated replication, and bootstrap methods.
  • Demonstration of how these techniques estimate sampling variances.
  • Illustrative examples of replication in complex survey analysis.

Conclusions:

  • Replication techniques are effective for variance estimation in complex survey data.
  • These methods facilitate reliable inference from survey results.
  • The jackknife, balanced repeated replication, and bootstrap are key tools for survey statisticians.