Missing-not-at-random Modeling
Missing-Not-At-Random Modeling is a statistical framework within implicit feedback modeling that specifically accounts for systematic patterns in missing data by assuming that the probability of data being missing depends on unobserved entries, thereby distinguishing it from missing-at-random and missing-completely-at-random mechanisms.
145
Publications
11.3K
Citations
353
Authors
199
Institutions
Publications per year
2017–2026
30
Parents
145
Deviance information criteria for missing data models
Gilles Celeux, Florence Forbes, Caroline Robert et al. · Bayesian Analysis · 2006 · 899 citations · Full text
Analyzing incomplete longitudinal clinical trial data
Geert Molenberghs · Biostatistics · 2004 · 385 citations
Analyzing incomplete longitudinal clinical trial data
Geert Molenberghs · Biostatistics · 2004 · 380 citations · Full text
1–5 of 145
353
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London School of Hygiene & Tropical Medicine, United Kingdom
9 publications · 654 citations
9
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5
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5
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4
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1–5 of 353
199
London School of Hygiene & Tropical Medicine
London, United Kingdom
8 h-index
11 publications
1K citations
Eli Lilly (United States)
Indianapolis, United States
5 h-index
15 publications
2.2K citations
KU Leuven
Leuven, Belgium
5 h-index
9 publications
417 citations

Hasselt University
Hasselt, Belgium
5 h-index
12 publications
915 citations
Transnational University Limburg
Diepenbeek, Belgium
5 h-index
8 publications
1.2K citations
The University of Texas at Austin
Austin, United States
4 h-index
4 publications
360 citations

University of Notre Dame
Notre Dame, United States
4 h-index
7 publications
195 citations

University of British Columbia
Vancouver, Canada
4 h-index
4 publications
448 citations
1–8 of 199
11 publications · 385 citations
11
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9 publications · 719 citations
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CSDA · 7 publications · 178 citations
7
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SEM · 6 publications · 319 citations
6
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Repository · 6 publications · 119 citations
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