Data Fabrication and Falsification
Data fabrication and falsification are serious forms of research misconduct involving intentional misrepresentation of research data. Fabrication means inventing data that were never actually collected; falsification means altering authentic data to change the meaning. Both undermine scientific integrity, waste research resources, and can harm research subjects and the public. Federal policy (42 CFR Part 93) formally defines these violations; detection is improving through statistical analysis tools and data transparency practices; prevention requires robust data governance and culture of accountability.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- U.S. Office of Research Integrity. (2005). Public Health Service Policy on Research Misconduct. 42 CFR Part 93. Definitions of fabrication and falsification. · URL
- Carlisle, J.B. (2017). Data Fabrication and Deviation in Statistics in Anesthesia Articles. Anesthesia, 72(2), 221–237. · URL
- Nuijten, M.B., Hartgerink, C.H., van Assen, M.A., et al. (2015). The Prevalence of Statistical Reporting Errors in Psychology (1985-2013). Behavior Research Methods, 48(4), 1205–1226. · DOI 10.3758/s13428-015-0664-2
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.