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Estimating variance components by using survey data

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  • Edward L. Korn
  • Barry I. Graubard

Abstract

Summary. Inflation‐type weighted estimators for variance components can be badly biased. Modified weighted estimators suggested in the literature are also badly biased for certain sampling designs. We propose new estimators for variance components, some of which are approximately unbiased regardless of the sampling design. These estimators require knowledge of the joint inclusion probabilities of the observations. The small sample properties of the estimators are studied via simulation for the simple one‐way random‐effects model. An application is given by using data from the US Hispanic Health and Nutrition Examination Survey.

Suggested Citation

  • Edward L. Korn & Barry I. Graubard, 2003. "Estimating variance components by using survey data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 175-190, February.
  • Handle: RePEc:bla:jorssb:v:65:y:2003:i:1:p:175-190
    DOI: 10.1111/1467-9868.00379
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    File URL: https://doi.org/10.1111/1467-9868.00379
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    Cited by:

    1. Sophia Rabe‐Hesketh & Anders Skrondal, 2006. "Multilevel modelling of complex survey data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(4), pages 805-827, October.
    2. M. Giovanna Ranalli & Giorgio E. Montanari & Cecilia Vicarelli, 2018. "Estimation of small area counts with the benchmarking property," METRON, Springer;Sapienza Università di Roma, vol. 76(3), pages 349-378, December.
    3. Woodward, Albert & Das, Abhik & Raskin, Ira E. & Morgan-Lopez, Antonio A., 2006. "An exploratory analysis of treatment completion and client and organizational factors using hierarchical linear modeling," Evaluation and Program Planning, Elsevier, vol. 29(4), pages 335-351, November.
    4. Yergeau, Marie-Eve, 2020. "Tourism and local welfare: A multilevel analysis in Nepal’s protected areas," World Development, Elsevier, vol. 127(C).

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