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A design‐based approach to small area estimation using a semiparametric generalized linear mixed model

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  • Hongjian Yu
  • Yueyan Wang
  • Jean Opsomer
  • Pan Wang
  • Ninez A. Ponce

Abstract

In small area estimation, non‐parametric models with penalized spline regression have been demonstrated to be a useful tool in creating granular area estimates to provide supplemental information where samples are few or non‐existent. This study further examines the ability of a semiparametric generalized linear mixed model to produce conforming estimates for multiple area levels. A mosaic analogy is used to describe this process. A design‐based jackknife method is employed for variance calculation.

Suggested Citation

  • Hongjian Yu & Yueyan Wang & Jean Opsomer & Pan Wang & Ninez A. Ponce, 2018. "A design‐based approach to small area estimation using a semiparametric generalized linear mixed model," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 1151-1167, October.
    • Handle: RePEc:bla:jorssa:v:181:y:2018:i:4:p:1151-1167
    DOI: 10.1111/rssa.12351
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    References listed on IDEAS

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