What Works for Whom? A Bayesian Approach to Channeling Big Data Streams for Public Program Evaluation

Mariel McKenzie Finucane, Ignacio Martinez and Scott Cody

Mathematica Policy Research Reports from Mathematica Policy Research

Abstract: In the coming years, public programs will 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.

Keywords: heterogeneous impacts; Bayesian statistics; adaptive design; hierarchical models; randomized control trials (search for similar items in EconPapers)
Pages: 14
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