ArticleTheory & psychology2025
Tools of the data detective: A review of statistical methods to detect data and result anomalies in psychology.
Article in Theory & psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In psychology, it is largely assumed that researchers collect real data and analyze them honestly-that is, it is assumed that data fabrication seldom occurs. While data fabrication is a rare phenomenon, estimates suggest that it occurs frequently enough to be a concern. To this end, statistical tools have been created to detect and deter data fabrication. Often, these tools either assess raw data, or assess summary statistical information. However, very few studies have attempted to review these tools, and of those that have, certain tools were excluded. The purpose of the present study was to review a collection of existing statistical tools to detect data fabrication, assess their strengths and limitations, and consider their place in psychological practice. The major strengths of the tools included their comprehensiveness and rigor, while their limitations were in their stringent criteria to run and in that they were impractical to implement.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.