26. Stratified Adaptive Cluster Sampling

  1. Steven K. Thompson

Published Online: 10 FEB 2012

DOI: 10.1002/9781118162934.ch26

Sampling, Third Edition

Sampling, Third Edition

How to Cite

Thompson, S. K. (2012) Stratified Adaptive Cluster Sampling, in Sampling, Third Edition, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781118162934.ch26

Author Information

  1. Simon Fraser University, Canada

Publication History

  1. Published Online: 10 FEB 2012
  2. Published Print: 23 FEB 2012

Book Series:

  1. Wiley Series in Probability and Statistics

Book Series Editors:

  1. Walter A. Shewhart and
  2. Samuel S. Wilks

ISBN Information

Print ISBN: 9780470402313

Online ISBN: 9781118162934

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Keywords:

  • stratified adaptive cluster sampling;
  • unbiased estimators

Summary

Stratified adaptive cluster sampling designs are important from a practical point of view because for many populations prior information exists on which an initial stratification can be based and yet the exact distribution or patterns of concentration of the population cannot be predicted. In conventional stratified sampling, units that are thought to be similar are grouped a priori into strata, based on prior information about the population or simple proximity of the units. Adaptive cluster sampling, on the other hand, provides a means of taking advantage of clustering tendencies in a population, when the locations and shapes of the clusters cannot be predicted prior to the survey. This chapter describes the sampling designs that combine the two methods. The chapter discusses estimators that are unbiased under the designs. The different unbiased estimators given in the chapter handle crossing of stratum boundaries in slightly different ways.

Controlled Vocabulary Terms

cluster sampling; estimator; stratified sampling