Spatial small area smoothing models for handling survey data with nonresponse.

ABSTRACT: Spatial smoothing models play an important role in the field of small area estimation. In the context of complex survey designs, the use of design weights is indispensable in the estimation process. Recently, efforts have been made in these spatial smoothing models, in order to obtain reliable estimates of the spatial trend. However, the concept of missing data remains a prevalent problem in the context of spatial trend estimation as estimates are potentially subject to bias. In this paper, we focus on spatial health surveys where the available information consists of a binary response and its associated design weight. Furthermore, we investigate the impact of nonresponse as missing data on a range of spatial models for different missingness mechanisms and different degrees of missingness

SUBMITTER: Watjou K 

PROVIDER: S-EPMC5585068 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature