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Some Open Questions on Multiple-Source Extensions of Adaptive-Survey Design Concepts and Methods

Author

Listed:
  • Stephanie Coffey, PhD.
  • Jaya Damineni
  • John Eltinge, PhD.
  • Anup Mathur, PhD.
  • Kayla Varela
  • Allison Zotti

Abstract

Adaptive survey design is a framework for making data-driven decisions about survey data collection operations. This paper discusses open questions related to the extension of adaptive principles and capabilities when capturing data from multiple data sources. Here, the concept of “design” encompasses the focused allocation of resources required for the production of high-quality statistical information in a sustainable and cost-effective way. This conceptual framework leads to a discussion of six groups of issues including: (i) the goals for improvement through adaptation; (ii) the design features that are available for adaptation; (iii) the auxiliary data that may be available for informing adaptation; (iv) the decision rules that could guide adaptation; (v) the necessary systems to operationalize adaptation; and (vi) the quality, cost, and risk profiles of the proposed adaptations (and how to evaluate them). A multiple data source environment creates significant opportunities, but also introduces complexities that are a challenge in the production of high-quality statistical information.

Suggested Citation

  • Stephanie Coffey, PhD. & Jaya Damineni & John Eltinge, PhD. & Anup Mathur, PhD. & Kayla Varela & Allison Zotti, 2023. "Some Open Questions on Multiple-Source Extensions of Adaptive-Survey Design Concepts and Methods," Working Papers 23-03, Center for Economic Studies, U.S. Census Bureau.
    • Handle: RePEc:cen:wpaper:23-03
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    File URL: https://www2.census.gov/library/working-papers/2023/adrm/ces/CES-WP-23-03.pdf
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    References listed on IDEAS

    as
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