Researchers, policymakers, and other stakeholders are often interested in obtaining survey estimates of quantities of interest for various subpopulations. This may include estimates for detailed geographic levels, for multiple sociodemographic groups, or for a combination of both. Frequently, the demand for estimates at granular levels exceeds what a survey’s sample size and design can support when estimation is done via traditional design-based estimation methods. Small area estimation involves exploiting relationships among domains and borrowing strength from multiple sources of information to improve inference relative to direct survey methods. This typically involves the use of models whose success depend heavily on the quality and predictive ability of the sources of information used. Possible sources of auxiliary information include administrative records, censuses, big data such as traffic or cell phone data, or previous vintages of the same survey. One rich source of information is that of other surveys. Carolina will give a review of the topic of combining information from multiple surveys in small area estimation, providing practical advice and a technical introduction, and illustrating with various applications. She will discuss reasons to combine surveys and give an overview of some of the most common types of models. This talk is primarily based on an invited review paper on the topic.
Global Network and ISWGHS joint webinar: Combining Surveys in Small Area Estimation
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