Methods for Research Synthesis: A Cross-Disciplinary Approach

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October 3, 2013 Workshop

View workshop video.

Download final program.

View agenda and download papers.

Description:

Methods for research synthesis, including systematic review, meta-analysis, and expert elicitation, are used in almost every field to combine the results of studies that address similar quantities or phenomena. These methods are often employed when estimating parameter values for policy analysis, such as the toxicity of a substance, the monetary value of risk reductions, or the effectiveness of different interventions. However, researchers often face difficult questions about how to choose among these methods and how to adapt each method to particular problems and available data. If used inappropriately, these approaches may yield misleading conclusions about the relative merits of alternative interventions, leading to undesirable policy outcomes.

This Harvard Center for Risk Analysis workshop is part of an interdisciplinary project to improve the use of these methods in policy analysis. Its goal is to promote evidence-based decision making. Its objectives include:

  1. Increasing cross-disciplinary communication and collaboration on methodological issues by bringing together experts from diverse fields to address common problems;
  2. Defining more rigorously the types of problems and data for which different synthesis methods are most appropriate, alone or in combination;
  3. Developing innovative approaches for addressing specific challenges in applying these methods; and,
  4. Identifying areas where further cross-disciplinary work will be particularly fruitful

The workshop provides an opportunity for presentation and discussion of invited papers on the application of these methods in diverse contexts. Papers  evaluate, for example, how a particular method should be applied in different contexts, or how different methods should be used for a particular application. Following the workshop, the papers will be revised and submitted for publication.

Major funding for this project is provided by the National Science Foundation, with additional support from the Harvard Superfund Research Program Research Translation Core, the Harvard University Center for the Environment, the European Association of Environmental and Resource Economists, Gradient, the Health Effects Institute, the Texas Commission on Environmental Quality, the Society for Risk Analysis Economics and Benefits Analysis Specialty Group, and the U.S. Department of Agriculture Economics Research Service.