Combining Estimates from Multiple Surveys

Combining estimates from multiple surveys can be very useful, especially when the question of interest cannot be addressed well by a single, existing survey. In this paper, we provide a brief review of methodology for combining estimates, with a focus on dual frame, weighting-based, joint-modeling, missing-data, and small-area methods. Many such methods are useful in situations outside the realm of combining estimates from surveys, such as combining information from surveys with administrative data and combining probability-sample data with non-probability sample, or “big” data. We also provide examples of comparability issues that must be kept in mind when information from different sources is being combined.

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