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.
원본 기록
방법의 원본 기록에서 그대로 복사된 인용입니다. 이로부터 수준별 검증이 추론되지 않습니다.
- 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
큐레이션된 주장
각각 자체 평가와 함께 증거 원장에 유지된 주장입니다.
원장에 주장 평가가 없는 경우 이 보기에서는 주장 평가를 만들지 않습니다.
관련 방법
방법 그래프에서 생성되었으며 기계가 제안한 관계로 표시됩니다 — 증거 주장이 추론되지 않습니다.