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Article 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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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12121900PMC
http://dx.doi.org/10.1177/09593543241311861DOI Listing

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