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Multistage Sampling

  • K. R. W. Brewer
  • Muhammad Hanif
Part of the Lecture Notes in Statistics book series (LNS, volume 15)

Abstract

Multistage sampling occupies a central role both in the theory and in the applications of unequal probability sampling. It was in the context of multistage sampling that unequal probability sampling was first suggested (Hansen and Hurwitz, 1943). There are in fact two quite different contexts in which unequal probability sampling is used:
  1. 1.

    Unistage unequal probability sampling of units such as factories, farms and businesses in large scale economic surveys. Here unequal probability sampling is used in place of stratification by size, and can be viewed as taking the size stratification idea to its logical conclusion (see Chapter 6).

     
  2. 2.

    Multistage unequal probability sampling in area surveys of individuals and households. Here multistage sampling is used partly to overcome the problem that lists of the ultimate sampling units are typically not available, and partly to reduce travel costs by ensuring that the sample units are geographically clustered. Unequal probability sampling, in this context, is used partly to reduce sampling errors and partly to ensure that the resulting area samples are conveniently structured.

     

Keywords

Unbiased Estimator Multistage Sampling Reduce Sampling Error Unequal Probability Sampling Base Variance Estimation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1983

Authors and Affiliations

  • K. R. W. Brewer
    • 1
  • Muhammad Hanif
    • 2
  1. 1.c/o Commonwealth Schools CommissionWoden, CanberraAustralia
  2. 2.Department of StatisticsEl-Fateh UniversityTripoliLibya (S.P.L.A.J.)

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