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What Works for Whom? A Bayesian Approach to Channeling Big Data Streams for Policy Analysis

Author

Listed:
  • Mariel McKenzie Finucane
  • Ignacio Martinez
  • Scott Cody

Abstract

In the coming years, public programs will continuously capture even more and richer data than they do now, including data from web-based tools used by participants in employment services, from tablet-based educational curricula, and from electronic health records for Medicaid beneficiaries, for example.

Suggested Citation

  • Mariel McKenzie Finucane & Ignacio Martinez & Scott Cody, "undated". "What Works for Whom? A Bayesian Approach to Channeling Big Data Streams for Policy Analysis," Mathematica Policy Research Reports bc0d75a1aca04c39b7e45226e, Mathematica Policy Research.
    • Handle: RePEc:mpr:mprres:bc0d75a1aca04c39b7e45226eb110ef5
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    File URL: https://www.mathematica.org/-/media/publications/pdfs/health/bayesian_approach_channeling_wp.pdf
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    Cited by:

    1. Robert G. Wood & Brian Goesling & Diane Paulsell, "undated". "Design for an Impact Study of Five Healthy Marriage and Relationship Education Programs and Strategies," Mathematica Policy Research Reports 01852acb9cbb4dd9afd6bc7cb, Mathematica Policy Research.

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