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On Minimizing the Risk of Bias in Randomized Controlled Trials in Economics

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  • P R W P
    7746
    On Minimizing the Risk of Bias
    in Randomized Controlled Trials in Economics
    Alex Eble
    Peter Boone
    Diana Elbourne
    Development Economics Vice Presidency
    Operations and Strategy Team
    July 2016
    WPS7746
    Public Disclosure AuthorizedPublic Disclosure AuthorizedPublic Disclosure AuthorizedPublic Disclosure Authorized
  • Produced by the Research Support Team
    Abstract
    e Policy Research Working Paper Series disseminates the ndings of work in progress to encourage the exchange of ideas about development
    issues. An objective of the series is to get the ndings out quickly, even if the presentations are less than fully polished. e papers carry the
    names of the authors and should be cited accordingly. e ndings, interpretations, and conclusions expressed in this paper are entirely those
    of the authors. ey do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and
    its aliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.
    P R W P 7746
    is paper is a product of the Operations and Strategy Team, Development Economics Vice Presidency. It is part of a
    larger eort by the World Bank to provide open access to its research and make a contribution to development policy
    discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org.
    e authors may be contacted at eble@tc.columbia.edu.
    Estimation of empirical relationships is prone to bias. Econ-
    omists have carefully studied sources of bias in structural
    and quasi-experimental approaches, but the randomized
    control trial (RCT) has only begun to receive such scrutiny.
    is paper argues that several lessons from medicine, derived
    from analysis of thousands of RCTs establishing a clear link
    between certain practices and biased estimates, can be used
    to reduce the risk of bias in economics RCTs. It identies
    the subset of these lessons applicable to economics and uses
    them to assess risk of bias in estimates from economics RCTs
    published between 2001 and 2011. In comparison to medi-
    cal studies, most economics studies examined do not report
    important details on study design necessary to assess risk of
    bias. Many report practices that suggest risk of bias, though
    this does not necessarily mean bias resulted. e paper
    concludes with suggestions on how to remedy these issues.
  • On Minimizing the Risk of Bias in Randomized Controlled Trials
    in Economics
    Alex Eble, Peter Boone, and Diana Elbourne
    JEL codes: C90, C93
    Keywords: Bias, randomization, RCTs, study design
    Alex Eble (corresponding author) is assistant professor of economics and education at Teachers College,
    Columbia University. His email is eble@tc.columbia.edu. Peter Boone is Chair of Effective Intervention, at
    the Centre for Economic Performance, London School of Economics. His email is pb@effint.org. Diana
    Elbourne is professor of healthcare evaluation at the London School of Hygiene and Tropical Medicine.
    Her email is diana.elbourne@lshtm.ac.uk. This paper was previously circulated under the title “Risk and
    Evidence of Bias in Randomized Controlled Trials in Economics”. The authors would like to thank Simon
    Johnson and Miranda Mugford for helpful conversations and Samuel Brown, Garret Christensen, Steven
    Durlauf, Morgan Hardy, Vernon Henderson, Paul Musgrave, Gareth Olds, Anja Sautmann, Tim Squires,
    David Weil, Hyunjoo Yang, and participants at NEUDC 2012, the PAA 2013 annual conference, Royal
    Economic Society 2013 annual conference, Brown University micro lunch and Georgetown University
    Quantitative Models seminar for many helpful comments, as well as generous input from the editor and
    three anonymous referees. We thank Effective Intervention for financial support. Eble gratefully
    acknowledges the financial support of the US National Science Foundation through a Graduate Research
    Fellowship and an IGERT Traineeship. All remaining errors are our own.

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On Minimizing the Risk of Bias in Randomized Controlled Trials in Economics

On Minimizing the Risk of Bias in Randomized Controlled Trials in Economics

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