Marginal Mean Models
Marginal Mean Models is a statistical modeling framework that belongs to the class of marginal structural models and is distinguished by its focus on estimating population-averaged effects of time-varying treatments while accounting for time-dependent confounding through inverse probability weighting.
120
Publications
11.2K
Citations
284
Authors
186
Institutions
Publications per year
2017–2026
27
Parents
120
1–5 of 120
284
9
h-index
8
h-index
University of North Carolina at Chapel Hill, United States
8 publications · 404 citations
8
h-index
7
h-index
6
h-index
1–5 of 284
186
Harvard University
Cambridge, United States
14 h-index
20 publications
3.6K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
12 h-index
22 publications
1.9K citations
University of Michigan
Ann Arbor, United States
10 h-index
15 publications
1.8K citations

Johns Hopkins University
Baltimore, United States
8 h-index
12 publications
1.8K citations
Cancer Research And Biostatistics
Seattle, United States
6 h-index
8 publications
882 citations
University of Washington
Seattle, United States
6 h-index
9 publications
943 citations
Universidad Torcuato Di Tella
Buenos Aires, Argentina
5 h-index
5 publications
514 citations
Universidad de Buenos Aires
Buenos Aires, Argentina
4 h-index
4 publications
424 citations
1–8 of 186
16 publications · 1.1K citations
15
h-index
13 publications · 2.4K citations
12
h-index
12 publications · 730 citations
11
h-index
4 publications · 116 citations
4
h-index
4 publications · 122 citations
4
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1–5