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A Causal Replication Framework for Designing and Assessing Replication Efforts.

Replication has long been a cornerstone for establishing trustworthy scientific results, but there remains considerable disagreement about what constitutes a replication, how results from these studies should be interpreted, and whether direct replication of results is even possible. This article ad...

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Published in:Zeitschrift für Psychologie Vol. 227; no. 4; pp. 280 - 293
Main Authors: Steiner, Peter M., Wong, Vivian C., Anglin, Kylie
Format: review tables/charts Journal Article
Published: Hogrefe Publishing GmbH 2019
Online Access:View this record in EBSCOhost
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      pub: Hogrefe Publishing GmbH
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        atl: A Causal Replication Framework for Designing and Assessing Replication Efforts.
      aug:
        au:
          Steiner, Peter M.
          Wong, Vivian C.
          Anglin, Kylie
        affil: Department of Human Development and Quantitative Methodology, University of Maryland, College Park, MD, USA
      sug:
        subj:
          Replication Studies Methods
          Measurement Issues and Assessments
          Causality
          Conceptual Framework
          Sampling Error
          Study Design
      ab: Replication has long been a cornerstone for establishing trustworthy scientific results, but there remains considerable disagreement about what constitutes a replication, how results from these studies should be interpreted, and whether direct replication of results is even possible. This article addresses these concerns by presenting the methodological foundations for a replication science. It provides an introduction to the causal replication framework, which defines "replication" as a research design that tests whether two (or more) studies produce the same causal effect within the limits of sampling error. The framework formalizes the conditions under which replication success can be expected, and allows for the causal interpretation of replication failures. Through two applied examples, the article demonstrates how the causal replication framework may be utilized to plan prospective replication designs, as well as to interpret results from existing replication efforts.
      pubtype: Academic Journal
      doctype:
        review
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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