Bayesian Inference for Social Policy Research

March 15, 2019
Topics:
Methods and Tools
Projects:
Exploring Bayesian Methods for Social Policy Research and Evaluation | Learn more about this project
Types:
Reports
Bayesian Inference for Social Policy Research Brief Cover
Download report (pdf)
  • File Size 330kb
  • Pages 6
  • Published 2019

Introduction

Bayesian methods are emerging as the primary alternative to the conventional frequentist approach to statistical inference. This brief provides an overview of the Bayesian perspective and highlights potential advantages of Bayesian inference over frequentist inference. In light of the increasing value and viability of Bayesian methods to contemporary policy debates, the brief outlines the following steps to advance Bayesian analysis in social policy research:

  • Extend methodological requirements in grant and contract proposal submission guidelines;
  • Develop requirements for evaluating publications that use Bayesian methods; and
  • Expand requirements for federal evidence reviews and clearinghouse submissions.

Citation

Kaplan, David (2019). Bayesian Inference for Social Policy Research, OPRE Report 2019-36, Washington, DC: Office of Planning, Research, and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services.

Last Reviewed: May 13, 2019