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Improving statistical reporting in psychology.

Anna-Lena Schubert1, Meike Steinhilber2, Heemin Kang3

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This paper introduces guidelines and a checklist for transparent statistical reporting in psychology. Adopting these standards enhances research credibility, reproducibility, and cumulative scientific progress.

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Area of Science:

  • Psychology
  • Quantitative Psychology
  • Research Methodology

Background:

  • Credible, reproducible, and interpretable psychological research relies on transparent statistical reporting.
  • Existing practices often lack clarity in planning and results stages.
  • Emerging best practices necessitate structured guidelines.

Purpose of the Study:

  • To provide a structured set of guidelines for reporting statistical analyses in quantitative psychology.
  • To emphasize clarity in both the planning and results stages of research.
  • To facilitate the implementation of transparent reporting through practical tools and examples.

Main Methods:

  • Outlining key decisions in hypothesis formulation, sample size, preregistration, data handling, model specification, and outcome interpretation.
  • Addressing both frequentist and Bayesian frameworks, and fixed vs. sequential designs.
  • Providing the Transparent Statistical Reporting in Psychology (TSRP) Checklist and a curated list of tools.

Main Results:

  • The guidelines cover essential aspects of statistical reporting, including effect sizes and null results.
  • A hypothetical study illustrates the practical application of recommended reporting standards.
  • The TSRP Checklist and accompanying tools are available to aid researchers.

Conclusions:

  • Adopting transparent statistical reporting standards improves the robustness of individual studies.
  • Enhanced reporting facilitates cumulative scientific progress through reliable meta-analyses and research syntheses.
  • Implementation of these guidelines bridges the gap between statistical theory and research practice.