Ignorable Missingness
Ignorable Missingness is a missingness mechanism in which the probability of data being missing depends only on observed variables, making the missing data process separable from the substantive model under the assumption of parameter distinctness and missing at random.
80
Publications
5.9K
Citations
174
Authors
129
Institutions
Publications per year
2017–2026
17
80
1–5 of 80
174
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h-index
5
h-index
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h-index
National Center for Health Statistics, United States
3 publications · 984 citations
3
h-index
1–5 of 174
129
Harvard University
Cambridge, United States
10 h-index
10 publications
3.2K citations

Pennsylvania State University
State College, United States
7 h-index
14 publications
385 citations
University of Chicago
Chicago, United States
4 h-index
5 publications
154 citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
4 h-index
8 publications
317 citations
University of Connecticut
Storrs, United States
3 h-index
3 publications
114 citations
University of Michigan
Ann Arbor, United States
3 h-index
5 publications
88 citations
National Cancer Institute
Bethesda, United States
3 h-index
3 publications
62 citations
The University of Texas at Austin
Austin, United States
2 h-index
2 publications
37 citations
1–8 of 129
10 publications · 337 citations
10
h-index
10 publications · 407 citations
10
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8 publications · 2.2K citations
8
h-index
CSDA · 3 publications · 87 citations
3
h-index
3 publications · 57 citations
3
h-index
1–5