Falsified Data Detection
Falsified Data Detection is a systematic methodological framework within research integrity science that identifies deliberate manipulations or fabrications in empirical data by distinguishing anomalous patterns indicative of intentional misconduct from legitimate variability in authentic research outputs.
89
Publications
6.2K
Citations
243
Authors
148
Institutions
Publications per year
2017–2026
32
Parents
89
Bernard Fisher, Stewart Anderson, Carol Redmond et al. · New England Journal of Medicine · 1995 · 1.5K citations · Full text
Uri Simonsohn · Psychological Science · 2013 · 224 citations
Business, Accountancy, Accounting +16
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148

Johns Hopkins University
Baltimore, United States
5 h-index
5 publications
389 citations
University of Washington
Seattle, United States
5 h-index
5 publications
389 citations
German Cancer Research Center
Heidelberg, Germany
3 h-index
8 publications
536 citations
Duke University
Durham, United States
3 h-index
3 publications
437 citations
Heidelberg University
Heidelberg, Germany
3 h-index
3 publications
344 citations

Lund University
Lund, Sweden
3 h-index
3 publications
344 citations

Universitair Ziekenhuis Leuven
Leuven, Belgium
2 h-index
2 publications
308 citations

University of Edinburgh
Edinburgh, United Kingdom
2 h-index
2 publications
308 citations
1–8 of 148
5 publications · 56 citations
5
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4 publications · 93 citations
4
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2 publications · 68 citations
2
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2 publications · 110 citations
2
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2 publications · 300 citations
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