Covariate selection for estimating the causal effect of control plans by using causal diagrams
By Manabu Kuroki, M. Miyakawa. 2003
48 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Sociology and Political Science, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/d2f6c1cdd3c467ffb204de1ae7e20a145ba92a23
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Emilija Perkovi'c
- Leonard Henckel
- Marloes H. Maathuis
- Peter Buhlmann
- Nicolai Meinshausen
- Mathias Drton
- Preetam Nandy
- Diego Colombo
In Sociology and Political Science
In Statistics and Probability
- Emilija Perkovi'c
- Leonard Henckel
- Marloes H. Maathuis
- Peter Buhlmann
- Nicolai Meinshausen
- Markus Kalisch
- Diego Colombo
- Mathias Drton
Citations in the corpus
- Graphical criteria for efficient total effect estimation via adjustment in causal linear models (2019, methodology): “Kuroki and Miyakawa (2003) and Kuroki and Cai (2004) adopt an approach that circumvents the difficulties of labeling individual covariates.”