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Meta-Analytic Methods to Detect Publication Bias in Behavior Science Research.

Art Dowdy1,2, Donald A Hantula3, Jason C Travers1

  • 1Department of Teaching and Learning, Temple University, Philadelphia, PA USA.

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|March 28, 2022
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Summary
This summary is machine-generated.

Publication bias, a concern in science, needs evaluation in behavior research, especially for single-case experimental designs. This study offers meta-analytic methods for assessing bias with or without grey literature.

Keywords:
behavior scienceevidence-based behavior analysismeta-analysispublication biasresearch-synthesissingle-case experimental design

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Area of Science:

  • Behavioral science research
  • Psychology
  • Single-case experimental designs

Background:

  • Publication bias is a significant concern across scientific disciplines.
  • Its prevalence and evaluation methods are less documented in behavior science fields.
  • Single-case experimental designs (SCEDs) present unique challenges for bias assessment.

Purpose of the Study:

  • To explore and present meta-analytic techniques for evaluating publication bias in behavior science research.
  • To provide guidance for researchers using or adapting these methods for SCEDs.
  • To address the challenges of identifying grey literature in meta-analyses.

Main Methods:

  • Description of meta-analytic techniques for examining publication bias when published and grey literature are available.
  • Presentation of alternative meta-analytic techniques for situations where grey literature is inaccessible.
  • Adaptation of methods primarily used for group design studies for SCEDs.

Main Results:

  • The study provides preliminary guidance on applying meta-analytic techniques to evaluate publication bias in behavior science.
  • Sample datasets and R scripts are offered to facilitate understanding and application of statistical analyses.
  • The research aims to increase understanding of publication bias within the behavior science domain.

Conclusions:

  • Evaluating publication bias is crucial for the integrity of behavior science research, particularly for SCEDs.
  • The presented meta-analytic techniques offer viable approaches for bias assessment, even with limited grey literature.
  • This work encourages behavior scientists to assess and address publication bias in their research.