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