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Unbalanced ranked set sampling for estimating a population proportion.

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  • المؤلفون: Chen H;Chen H; Stasny EA; Wolfe DA
  • المصدر:
    Biometrics [Biometrics] 2006 Mar; Vol. 62 (1), pp. 150-8.
  • نوع النشر :
    Journal Article; Research Support, U.S. Gov't, Non-P.H.S.
  • اللغة:
    English
  • معلومة اضافية
    • المصدر:
      Publisher: Biometric Society Country of Publication: United States NLM ID: 0370625 Publication Model: Print Cited Medium: Print ISSN: 0006-341X (Print) Linking ISSN: 0006341X NLM ISO Abbreviation: Biometrics Subsets: MEDLINE
    • بيانات النشر:
      Publication: Alexandria Va : Biometric Society
      Original Publication: Washington.
    • الموضوع:
      Demography* ; Sampling Studies*; Data Interpretation, Statistical ; Humans ; Nutrition Surveys ; Reproducibility of Results
    • نبذة مختصرة :
      The application of ranked set sampling (RSS) techniques to data from a dichotomous population is currently an active research topic, and it has been shown that balanced RSS leads to improvement in precision over simple random sampling (SRS) for estimation of a population proportion. Balanced RSS, however, is not in general optimal in terms of variance reduction for this setting. The objective of this article is to investigate the application of unbalanced RSS in estimation of a population proportion under perfect ranking, where the probabilities of success for the order statistics are functions of the underlying population proportion. In particular, the Neyman allocation, which assigns sample units for each order statistic proportionally to its standard deviation, is shown to be optimal in the sense that it leads to minimum variance within the class of RSS estimators that are simple averages of the means of the order statistics. We also use a substantial data set, the National Health and Nutrition Examination Survey III (NHANES III) data, to demonstrate the feasibility and benefits of Neyman allocation in RSS for binary variables.
    • الموضوع:
      Date Created: 20060318 Date Completed: 20060721 Latest Revision: 20061115
    • الموضوع:
      20231215
    • الرقم المعرف:
      10.1111/j.1541-0420.2005.00435.x
    • الرقم المعرف:
      16542241