Variable Selection For Heterogeneity
Variable Selection for Heterogeneity is a methodological framework within causal inference that identifies covariates which systematically modify treatment effects in order to distinguish heterogeneous from homogeneous response patterns across subpopulations.
23
Publications
1.1K
Citations
62
Authors
54
Institutions
Publications per year
2017–2026
5
23
Variable selection in regression with compositional covariates
Wei Lin, Peijun Shi, Rui Feng et al. · Biometrika · 2014 · 269 citations
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54
Nanyang Technological University
Singapore, Singapore
4 h-index
6 publications
178 citations

Beijing University of Technology
Beijing, China
3 h-index
5 publications
139 citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
3 h-index
6 publications
521 citations
University of Pennsylvania
Philadelphia, United States
2 h-index
5 publications
1.1K citations
Vienna University of Economics and Business
Vienna, Austria
2 h-index
2 publications
51 citations
Yale University
New Haven, United States
2 h-index
2 publications
24 citations
University of Iowa
Iowa City, United States
2 h-index
2 publications
24 citations
University of Chinese Academy of Sciences
Beijing, China
2 h-index
5 publications
62 citations
1–8 of 54
2 publications · 51 citations
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1 publications · 14 citations
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1 publications · 11 citations
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1 publications · 179 citations
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1 publications · 22 citations
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