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Correspondence bias, also referred to as the fundamental attribution error, describes the tendency to attribute another person’s behavior to internal characteristics rather than situational influences. This cognitive bias leads individuals to overlook external factors that may be influencing actions, thereby fostering potentially inaccurate assessments of others’ intentions and dispositions.Empirical Evidence for Correspondence BiasResearch has consistently demonstrated the...
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Assessing Correspondence Between Experimental and Nonexperimental Estimates in Within-Study Comparisons.

Peter M Steiner1, Vivian C Wong2

  • 11 Department of Educational Psychology, University of Wisconsin-Madison, Madison, WI, USA.

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Summary

Within-study comparisons (WSC) assess if nonexperimental designs match randomized controlled trials. This study evaluates correspondence measures for WSCs, recommending a combined significance and equivalence testing approach for robust results.

Keywords:
correspondence measurescorrespondence testequivalence testquasi-experimentsreplicationwithin-study comparison

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Health Services Research

Background:

  • Within-study comparison (WSC) designs evaluate nonexperimental study methods against randomized controlled trials (RCTs).
  • A key challenge in WSCs is selecting appropriate criteria to determine if nonexperimental and experimental results replicate.
  • Assessing the validity of nonexperimental research designs is crucial for real-world application.

Purpose of the Study:

  • To examine various distance-based correspondence measures for assessing agreement between nonexperimental and experimental estimates in WSCs.
  • To evaluate the statistical properties of common correspondence measures using a simulation study.
  • To propose a novel, integrated framework combining significance and equivalence testing for WSC analysis.

Main Methods:

  • Simulation study to assess statistical properties of distance-based correspondence measures.
  • Comparison of traditional significance testing with equivalence testing approaches.
  • Development and evaluation of a combined significance and equivalence testing framework.

Main Results:

  • Identified limitations in existing distance-based correspondence measures for WSCs.
  • Demonstrated the utility of a simulation approach for evaluating correspondence measures.
  • The proposed combined testing framework offers a more straightforward and robust method for WSC analysis.

Conclusions:

  • The choice of correspondence measures significantly impacts WSC outcomes.
  • A combined significance and equivalence testing approach provides a reliable method for assessing replication in WSCs.
  • Practical guidance is offered for interpreting WSC results and enhancing the validity of nonexperimental research.