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Design-Based Approaches to Causal Replication Studies.

Vivian C Wong1, Kylie Anglin2, Peter M Steiner3

  • 1University of Virginia, Charlottesville, VA, USA. vcw2n@virginia.edu.

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Summary
This summary is machine-generated.

This study introduces design-based approaches for planning systematic replication studies, addressing the lack of methodological consensus. It uses the Causal Replication Framework (CRF) to evaluate replicability and identify variation sources.

Keywords:
Causal inferenceOpen scienceReplication

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Area of Science:

  • Methodology
  • Research Design
  • Scientific Replication

Background:

  • Growing interest in scientific replication highlights a need for standardized methodological guidance.
  • Current literature lacks a consensus on best practices for designing and implementing replication studies.
  • Existing approaches often fail to systematically address the assumptions underlying successful replication.

Purpose of the Study:

  • To present design-based approaches for planning systematic replication studies.
  • To introduce the Causal Replication Framework (CRF) for formalizing replication assumptions.
  • To provide a framework for evaluating replicability and diagnosing causes of replication failure.

Main Methods:

  • Derivation of a general approach from the Causal Replication Framework (CRF).
  • Systematic testing of CRF assumptions, categorized as replication design and individual study design requirements.
  • Description of various research designs suitable for replication efforts.
  • Demonstration of combining multiple designs in systematic replication.

Main Results:

  • Replication failure is linked to violations of CRF assumptions.
  • Design-based approaches systematically test CRF assumptions to assess replicability.
  • Methods are provided to identify sources of effect variation when replication fails.
  • Diagnostic measures are proposed to evaluate CRF assumption fulfillment in practice.

Conclusions:

  • Design-based approaches offer a structured method for planning and executing systematic replication studies.
  • The Causal Replication Framework (CRF) provides a formal basis for understanding and evaluating replication success.
  • This framework aids in assessing the reliability of research findings and understanding variability in effect sizes.