Missing Data Patterns
Missing Data Patterns is a methodological construct that identifies and classifies the systematic arrangements or configurations in which data values are absent across variables and observations in a dataset, distinguishing it from general data incompleteness by focusing on the structural regularity of omissions.
407
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61.2K
Citations
1.4K
Authors
620
Institutions
Publications per year
2017–2026
109
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407
Statistical Analysis with Missing Data
Subir Ghosh, Roderick J. A. Little, Donald B. Rubin · Technometrics · 1988 · 3.1K citations
Statistical Analysis With Missing Data
Nicole A. Lazar · Technometrics · 2003 · 2.5K citations
Statistical Analysis with Missing Data
Roderick J. A. Little, Donald B. Rubin · Population · 1988 · 2.1K citations
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London School of Hygiene & Tropical Medicine, United Kingdom
4 publications · 350 citations
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London School of Hygiene & Tropical Medicine, United Kingdom
3 publications · 124 citations
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Harvard University
Cambridge, United States
11 h-index
33 publications
1.2K citations
University of Michigan
Ann Arbor, United States
8 h-index
15 publications
1.4K citations
University of California, Los Angeles
Los Angeles, United States
8 h-index
11 publications
2.3K citations

Johns Hopkins University
Baltimore, United States
8 h-index
17 publications
573 citations
Yale University
New Haven, United States
6 h-index
15 publications
1.4K citations
University of Cambridge
Cambridge, United Kingdom
6 h-index
14 publications
441 citations

Centre National de la Recherche Scientifique
Paris, France
6 h-index
12 publications
534 citations
Massachusetts Institute of Technology
Cambridge, United States
5 h-index
8 publications
3.5K citations
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Repository · 9 publications · 236 citations
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7 publications · 351 citations
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