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Ensuring Transparency and Trust in Supervised-Machine-Learning Studies: A Checklist for Psychological Researchers

  • Hanyi Min
  • Feng Guo
  • Tianjun Sun
  • Mengqiao Liu
  • Frederick L. Oswald

Abstract

Machine-learning (ML) algorithms are being rapidly incorporated into the work of psychologists given their capability and flexibility in analyzing large-scale, complex, or otherwise messy data sets. In this context and in the spirit of open science, ML ...
Open AccessResearch articleFirst published Mar 12, 2026
Open materials
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Beyond Statistical Myopia: Replying to a Misguided Critique of Mind–Body Research

  • Peter J. Aungle
  • Daniel L. Chen
  • Nicholas P. Holmes

Abstract

In response to Gelman and Brown’s recent critique of Aungle and Langer, we argue that their article illustrates how narrow statistical reasoning and selective literature review can misrepresent and undermine credible scientific findings. Using their ...
Open AccessArticle commentaryFirst published Feb 25, 2026
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When Do Interaction/Moderation Effects Stabilize in Linear Regression?

  • Andrew Castillo
  • Joshua D. Miller
  • Colin Vize
  • David A. A. Baranger
  • Donald R. Lynam

Abstract

Two-way interaction effects in linear regression occur when the relation between two variables changes depending on the level of a third. Despite their frequent use, interactions are notoriously difficult to estimate accurately and test for statistical ...
Open AccessResearch articleFirst published Feb 19, 2026
Open dataOpen materialsPreregistred
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Measurement-Reporting Practices in Social-and-Personality-Psychology Articles

  • Katherine M. Lawson
  • Julia G. Bottesini
  • Linh D. Khong
  • Simine Vazire

Abstract

Psychological scientists are increasingly acknowledging the importance of transparency for research integrity. In the present study, we examined one important facet of transparency: providing enough information about measures so that readers can evaluate ...
Open AccessResearch articleFirst published Feb 12, 2026
Open dataOpen materialsPreregistred
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Identifying Careless Survey Respondents Through Machine Learning Using Responses to a Gibberish Scale

  • Leah Bloy
  • Yehezkel Resheff
  • Avraham Kluger
  • Nechumi Malovicki-Yaffe

Abstract

Invalid responses pose a significant risk of distorting survey data, compromising statistical inferences, and introducing errors in conclusions drawn from surveys. Given the pivotal role of surveys in research, development, and decision-making, it is ...
Open AccessResearch articleFirst published Oct 9, 2025
Open dataOpen materialsPreregistred
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Publication Bias in Academic Decision-Making in Clinical Psychology

  • Louis Schiekiera
  • Kristina Eichel
  • Felicitas Heßelmann
  • Jacqueline Sachse
  • Sophie P. Müller
  • Helen Niemeyer

Abstract

Review studies suggest that results that are statistically significant or consistent with hypotheses are preferred in the publication process and in reception. The mechanisms underlying this bias remain unclear, and prior research has focused on between-...
Open AccessResearch articleFirst published Sep 25, 2025
Open materialsPreregistred
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A Window Into the State of the Science: Current Reporting Practices Related to Generalizability in MRI and Functional-MRI Studies

  • Arianna M. Gard
  • Deena Shariq
  • Alison A. Albrecht
  • Alaina Lurie
  • Hyung Cho Kim
  • Colter Mitchell
  • Luke W. Hyde

Abstract

Concerns for the replicability, reliability, and generalizability of MRI and functional MRI (fMRI) research have led to debates over the contributions of sample size, open-science practices, and recruitment methods, particularly in the psychological ...
Open AccessResearch articleFirst published Sep 15, 2025
Open dataOpen materials
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Bridging Null Hypothesis Testing and Estimation: A Practical Guide to Statistical Conclusion Drawing From Research in Psychology

  • Henk A. L. Kiers
  • Jorge N. Tendeiro

Abstract

A well-known problem of null hypothesis significance testing is that it cannot be used to find support for the null hypothesis. A common solution for this is to replace the exact 0 value by an interval associated with values that are close to 0. This ...
Open AccessResearch articleFirst published Sep 3, 2025
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Citing Decisions in Psychology: A Roadblock to Cumulative and Inclusive Science

  • Katherine M. Lawson
  • Brett A. Murphy
  • Jovani Azpeitia
  • Ella J. Lombard
  • Terrènce J. Pope

Abstract

Citations are the main avenue through which scholarly contributions are recognized. However, decisions about what to cite (or not cite) are often made without much systematic thought. Suboptimal citing practices undermine psychological science. Yet ...
Open AccessResearch articleFirst published Sep 3, 2025
Open dataOpen materialsPreregistred
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From Experiments to Policy Insights: Generalizing Causal Effects From Study Samples to Target Populations

  • Wen Wei Loh
  • Dongning Ren

Abstract

Psychological science holds substantial promise for informing policy decisions but faces challenges in realizing its potential. One widely recognized challenge is bridging the gap between the nonrepresentative study samples commonly used to evaluate ...
Open AccessResearch articleFirst published Aug 21, 2025
Open dataOpen materials
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