G-methods
G-Methods is a class of statistical techniques in longitudinal causal inference that encompasses marginal structural models, g-computation, and g-estimation, distinguished by its use of explicit modeling of treatment and weighting or standardization to adjust for time-varying confounders affected by prior exposure.
61
Publications
7.4K
Citations
195
Authors
130
Institutions
Publications per year
2017–2026
24
61
Methods for dealing with time‐dependent confounding
Rhian Daniel, Simon Cousens, Bianca De Stavola et al. · Statistics in Medicine · 2012 · 383 citations
1–5 of 61
195
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3
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3
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3
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University of North Carolina at Chapel Hill, United States
3 publications · 1.7K citations
3
h-index
1–5 of 195
130
Harvard University
Cambridge, United States
8 h-index
13 publications
2.6K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
5 h-index
12 publications
2.5K citations
Inserm
Paris, France
5 h-index
20 publications
1.4K citations
Université de Tours
Tours, France
5 h-index
19 publications
1.3K citations

Nantes Université
Nantes, France
5 h-index
20 publications
1.4K citations

University of Toronto
Toronto, Canada
4 h-index
5 publications
197 citations
University of California, Berkeley
Berkeley, United States
4 h-index
10 publications
1.8K citations
London School of Hygiene & Tropical Medicine
London, United Kingdom
3 h-index
7 publications
1.7K citations
1–8 of 130
7 publications · 617 citations
7
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AJE · 5 publications · 1.1K citations
5
h-index
3 publications · 93 citations
3
h-index
3 publications · 2K citations
3
h-index
3 publications · 126 citations
3
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1–5