Missing Data Treatment
Missing Data Treatment is a methodological approach in morphological phylogenetics that constitutes the systematic strategy for addressing absent or inapplicable character states in cladistic analysis to minimize bias and error in phylogenetic inference.
121
Publications
11.6K
Citations
317
Authors
213
Institutions
Publications per year
2017–2026
35
121
Missing Data, Incomplete Taxa, and Phylogenetic Accuracy
John J. Wiens · Systematic Biology · 2003 · 663 citations
1–5 of 121
317
10
h-index
2
h-index
2
h-index
2
h-index
2
h-index
1–5 of 317
213
Stony Brook University
Stony Brook, United States
7 h-index
10 publications
2.7K citations
Natural History Museum
London, United Kingdom
7 h-index
14 publications
775 citations
University of Oxford
Oxford, United Kingdom
5 h-index
7 publications
1K citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
7 publications
711 citations

Centre National de la Recherche Scientifique
Paris, France
4 h-index
6 publications
408 citations
University of Arizona
Tucson, United States
4 h-index
6 publications
1.2K citations

American Museum of Natural History
New York, United States
4 h-index
7 publications
593 citations
State University of New York
Albany, United States
3 h-index
3 publications
862 citations
1–8 of 213
21 publications · 4K citations
21
h-index
8 publications · 659 citations
8
h-index
MBE · 4 publications · 677 citations
4
h-index
3 publications · 621 citations
3
h-index
JSE · 2 publications · 184 citations
2
h-index
1–5