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  • Realist synthesis: an introduction

    This guide, written by Ray Pawson, Trisha Greenhalgh, Gill Harvey and Kieran Walshe for the ESRC Research Methods Programme, provides an introduction to using realist synthesi
    Resource

  • 2017 International realist conference

    We've got our head in realism this week, partly because early-bird registrations for the 2017 International Realist Conference close soon, and partly because we've been shown Chris Lysy's realist cartoon series (commissioned by the Rameses
    Blog

  • Evaluating the environmental impact of personal protective equipment (PPE) in the COVID-19 pandemic

    This Footprint Evaluation case study explores the feasibility and value of considering environmental sustainability in the evaluation of personal protective equipment (PPE) provisioning during the COVID-19 pandemic.
    Resource

  • Regression discontinuity

    Regression Discontinuity Design (RDD) is a quasi-experimental evaluation option that measures the impact of an intervention, or treatment, by applying a treatment assignment mechanism based on a continuous eligibility index which is a varia
    Method

  • Evidence-based policy: A realist perspective

    This book, written by Ray Pawson, provides a critique of the meta-analytic approach and argues that the realist synthesis is a better way of understanding program theory, therefore enabling properly targeted policies to address the con
    Resource

  • Quasi-experimental methods for impact evaluations

    This video lecture, given by Dr Jyotsna Puri for the Asian Development Bank (ADB) and the International Initiative for Impact Evaluation (3ie), demonstrates how the use of quasi-experimental methods can circumvent the challenge of creating
    Resource

  • Quasi-experimental design and methods

    This guide, written by Howard White and Shagun Sabarwal for UNICEF looks at the use of quasi-experimental design and methods in impact evaluation.
    Resource

  • UNICEF webinar: Quasi-experimental design and methods

    What is the main difference between quasi-experiments and RCTs? How can I measure impact when establishing a control group is not an option?
    Resource

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