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Murthy’s Estimator in Unequal Probability Inverse Adaptive Cluster Sampling

Author

Listed:
  • Prayad Sangngam

Abstract

This paper derives a Murthy’s unbiased estimator of population total under unequal probability inverse sampling. A general unequal probability inverse sampling is combined with adaptive cluster sampling. An unbiased estimator of population total and its variance estimator are given using Murthy’s approach. The general unequal probability inverse adaptive cluster sampling and general equal probability inverse adaptive cluster sampling are compared using simulation study based on real life data. The results indicate that the general unequal probability inverse adaptive cluster sampling has a small coefficient of variation for estimates compared to equal probability inverse adaptive cluster sampling. When the coefficients of correlation between study variable and probability of selection units increase, the coefficient of variation decreases.

Suggested Citation

  • Prayad Sangngam, 2012. "Murthy’s Estimator in Unequal Probability Inverse Adaptive Cluster Sampling," Modern Applied Science, Canadian Center of Science and Education, vol. 6(11), pages 1-20, November.
    • Handle: RePEc:ibn:masjnl:v:6:y:2012:i:11:p:20
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    References listed on IDEAS

    as
    1. Mary C. Christman & Feng Lan, 2001. "Inverse Adaptive Cluster Sampling," Biometrics, The International Biometric Society, vol. 57(4), pages 1096-1105, December.
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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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