Weighted Estimating Equations
Weighted Estimating Equations is a statistical method for parameter estimation in the presence of missing data, in which observation-specific weights are incorporated into estimating equations to account for unequal probabilities of missingness, thereby yielding consistent and asymptotically normal estimators under misspecified or correct models.
89
Publications
10.2K
Citations
167
Authors
104
Institutions
Publications per year
2017–2026
8
Variants
Wee
Parents
89
1–5 of 89
167
7
h-index
5
h-index
University of North Carolina at Chapel Hill, United States
4 publications · 629 citations
4
h-index
4
h-index
3
h-index
1–5 of 167
104
Fred Hutch Cancer Center
Seattle, United States
7 h-index
7 publications
3.4K citations
Dana-Farber Cancer Institute
Boston, United States
5 h-index
5 publications
299 citations
Harvard University
Cambridge, United States
5 h-index
8 publications
6.3K citations
Columbia University
New York, United States
4 h-index
4 publications
276 citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
4 h-index
8 publications
2.1K citations

Pennsylvania State University
State College, United States
4 h-index
4 publications
243 citations

Indian Statistical Institute
Kolkata, India
3 h-index
3 publications
164 citations
Medical University of South Carolina
Charleston, United States
3 h-index
3 publications
158 citations
1–8 of 104
12 publications · 352 citations
11
h-index
10 publications · 3.9K citations
10
h-index
7 publications · 452 citations
7
h-index
CSDA · 4 publications · 158 citations
4
h-index
4 publications · 178 citations
4
h-index
1–5