Sequential Causal Inference
Sequential Causal Inference is a longitudinal causal inference framework that specifically addresses the identification and estimation of causal effects in settings where treatments, confounders, and outcomes evolve over time in a temporal sequence, distinguishing itself by modeling the dynamic, time-varying nature of interventions and their cumulative impacts on outcomes.
22
Publications
887
Citations
66
Authors
43
Institutions
Publications per year
2017–2026
6
Variants
Dynamic Causal Inference
22
Wendy B. London, Christopher Frantz, Laura Campbell et al. · Journal of Clinical Oncology · 2010 · 123 citations · Full text
Medicine, Oncology, Pharmacotherapy +13
Jon Michael Gran, Kjetil Røysland, Marcel Wolbers et al. · Statistics in Medicine · 2010 · 88 citations
1–5 of 22
66
Frontier Science & Technology Research Foundation, Inc., United States
2 publications · 36 citations
2
h-index
2
h-index
1
h-index
1
h-index
1
h-index
1–5 of 66
43
Frontier Science & Technology Research Foundation, Inc.
Boston, United States
2 h-index
2 publications
36 citations
Universidade de São Paulo
São Paulo, Brazil
1 h-index
1 publications
10 citations
Inserm
Paris, France
1 h-index
1 publications
25 citations
Columbia University
New York, United States
1 h-index
2 publications
40 citations
National University of Singapore
Singapore, Singapore
1 h-index
1 publications
19 citations
Hospital for Tropical Diseases
Hanoi, Vietnam
1 h-index
1 publications
88 citations

University Hospital of Bern
Bern, Switzerland
1 h-index
1 publications
88 citations
Amsterdam Neuroscience
Amsterdam, The Netherlands
1 h-index
1 publications
29 citations
1–8 of 43
3 publications · 124 citations
3
h-index
Repository · 2 publications · 46 citations
2
h-index
Repository · 1 publications · 11 citations
1
h-index
1 publications · 12 citations
1
h-index
Repository · 1 publications · 58 citations
1
h-index
1–5