A measurement error model approach to survey data integration: combining information from two surveys

Abstract

Combining information from several surveys from the same target population is an important practical problem in survey sampling. The paper is motivated by work that authors undertook, sponsored by the Food and Nutrition Technical Assistance III Project (FANTA), with funding from the U.S. Agency for International Development (USAID) Bureau of Food Security (BFS). In the project, two surveys were conducted independently for some areas and we present a measurement error model approach to integrate mean estimates obtained from the two surveys. The predicted values for the counterfactual outcome are used to create composite estimates for the overlapped areas. An application of the technique to the project is provided.