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Analysis of Adaptive Cluster Sampling Utilizing Standard Software Packages Without Complex Programming

Analysis of Adaptive Cluster Sampling Utilizing Standard Software Packages Without Complex Programming

Original Research ArticleNov 12, 2018Vol. 5 No. 1 (2005)

Abstract

Simple random sampling with or without replacement is the easiest to analyze using standard software, such as SAS, SPSS, Minitab, etc. Better population estimates can be obtained through more complex sampling design, but this introduces analysis issues. For example, regression is very straightforward with simple random sampling, but this is not always the case when more complicated sampling designs are used, such as adaptive cluster sampling. A serious concern with regression estimates introduced with many complicated designs is lack of independence, a necessary assumption. This paper covers an effective manner to analyze data collected from adaptive cluster sampling designs using standard software. Also, included is sample SAS code.

Keywords:  Adaptive cluster sampling, Hansen-Hurwitz, SAS

Corresponding author: E-mail: dryer@hotmail.com , ctchao@email.stat.ncku.edu.tw

How to Cite

Dryver*, A. L. ., & Chao, C. . (2018). Analysis of Adaptive Cluster Sampling Utilizing Standard Software Packages Without Complex Programming. CURRENT APPLIED SCIENCE AND TECHNOLOGY, 200-208.

References

  • Thompson, S.K. 1990 Adaptive Cluster Sampling. Journal of the American Statistical Association 85 1050-1059.
  • Hanselman, D.H., Quinn, T.J., Lunsford, D, Heifetz, J and Clausen, D 2003 Applications in adaptive cluster sampling of Gulf of Alaska rockfish. Fishery Bulletin 101(3), 501-513.
  • Conners, M.E. and Schwager, S.J. 2002 The use of adaptive cluster sampling for hydroacoustic surveys. Ices Journal of Marine Science 59(6), 1314-1325.
  • Lo, N. CH, Griffith, D and Hunter, JR 1997 Using a restricted adaptive cluster sampling to estimate Pacific hake larval abundance, California Cooperative Oceanic Fisheries Investigations Reports 38: 103-113.
  • Smith, D.R., Conroy, M.J. and Brakhage, D.H. 1995 Efficiency of adaptive cluster sampling for estimating density of wintering waterfowl. Biometrics 51 777-788.

Author Information

Arthur L. Dryver*

School of Applied Statistics, National Institute of Development Association, Bangkok, Thailand

Chang-Tai Chao

Department of Statistics, National Cheng-Kung University, Taiwan

About this Article

Journal

Vol. 5 No. 1 (2005)

Type of Manuscript

Original Research Article

Keywords

Adaptive cluster sampling, Hansen-Hurwitz, SAS

Published

12 November 2018