Semiparametric Efficiency is a theoretical construct in longitudinal causal inference that characterizes the optimal asymptotic variance achievable by an estimator under a semiparametric model, distinguishing it from fully parametric or nonparametric efficiency by incorporating both finite-dimensional parameters of interest and infinite-dimensional nuisance parameters.
274
Publications
25.4K
Citations
390
Authors
234
Institutions
Publications per year
2017–2026
53
Publications
274
1–5 of 274
Authors
390
- AA
12
h-index
- RJ
10
h-index
- YM
10
h-index
- JM
9
h-index
- WK
8
h-index
1–5 of 390
Institutions
234
Harvard University
Cambridge, United States
17 h-index
31 publications
4.4K citations
University of California, Berkeley
Berkeley, United States
15 h-index
31 publications
5.1K citations
Texas A&M University
College Station, United States
14 h-index
28 publications
1.6K citations
North Carolina State University
Raleigh, United States
11 h-index
13 publications
790 citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
10 h-index
23 publications
681 citations
University of Michigan
Ann Arbor, United States
9 h-index
13 publications
1.2K citations
University of Washington
Seattle, United States
8 h-index
8 publications
398 citations
Yale University
New Haven, United States
7 h-index
11 publications
1.4K citations
1–8 of 234
Venues
- The Annals of Statistics
29 publications · 2.9K citations
22
h-index
- Journal of the American Statistical Association
25 publications · 2.9K citations
21
h-index
- Biometrika
18 publications · 1.9K citations
15
h-index
- Econometric Theory
13 publications · 457 citations
12
h-index
- Econometrica
12 publications · 7.4K citations
12
h-index
1–5