Missing Data Impact Analysis
Missing Data Impact Analysis is a methodological framework within the domain of Sample Ratio Mismatch Detection that systematically evaluates the extent to which missing data distorts observed sample ratios and biases inferential outcomes in experimental studies.
74
Publications
6.7K
Citations
274
Authors
197
Institutions
Publications per year
2017–2026
21
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The poor availability of psychological research data for reanalysis.
Jelte M. Wicherts, Denny Borsboom, Judith Kats et al. · American Psychologist · 2006 · 572 citations
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197
University of Pennsylvania
Philadelphia, United States
4 h-index
12 publications
507 citations
The University of Texas Southwestern Medical Center
Dallas, United States
4 h-index
12 publications
292 citations
Yale University
New Haven, United States
4 h-index
11 publications
947 citations

Johns Hopkins University
Baltimore, United States
3 h-index
5 publications
143 citations
United States Food and Drug Administration
Silver Spring, United States
3 h-index
8 publications
727 citations

University of London
London, United Kingdom
3 h-index
3 publications
586 citations

The University of Melbourne
Melbourne, Australia
3 h-index
5 publications
114 citations

University of Amsterdam
Amsterdam, The Netherlands
2 h-index
2 publications
623 citations
1–8 of 197
5 publications · 395 citations
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2 publications · 27 citations
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2 publications · 84 citations
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2 publications · 510 citations
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2 publications · 100 citations
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