Missing data affect nearly every discipline by complicating the statistical analysis of collected
data. But since the 1990s, there have been important developments in the statistical …

Supplement to “Approaches to Improving Survey-Weighted Estimates”. The Supplementary
Material includes the density plots of the size variables, and dot plots summarizing the …

Background Childhood malnutrition is a major public health issue in Sub-Saharan Africa
(SSA) and 61.4 million children under the age of five years in the region are stunted …

It has historically been a challenge to perform Bayesian inference in a design-based survey
context. The present paper develops a Bayesian model for sampling inference in the …

In response to these challenges, the US Census Bureau has recently formed a new
Research and Methodology Directorate. Model-Based Inference The model-based …

Outside of the survey sampling literature, samples are often assumed to be generated by a
simple random sampling process that produces independent and identically distributed (IID) …

Obtaining reliable estimates about health outcomes for areas or domains where only few to
no samples are available is the goal of small area estimation (SAE). Often, we rely on health …

Small area estimation (SAE) entails estimating characteristics of interest for domains, often
geographical areas, in which there may be few or no samples available. SAE has a long …

Multiple imputation (MI) is a well-established method to handle item-nonresponse in sample
surveys. Survey data obtained from complex sampling designs often involve features that …

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 …