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pro vyhledávání: '"Santacatterina, Michele"'
Autor:
Kallus Nathan, Santacatterina Michele
Publikováno v:
Journal of Causal Inference, Vol 10, Iss 1, Pp 123-140 (2022)
In causal inference, a variety of causal effect estimands have been studied, including the sample, uncensored, target, conditional, optimal subpopulation, and optimal weighted average treatment effects. Ad hoc methods have been developed for each est
Externí odkaz:
https://doaj.org/article/899d97d9d0df482abd9d770f2809d804
Autor:
Kallus Nathan, Santacatterina Michele
Publikováno v:
Journal of Causal Inference, Vol 9, Iss 1, Pp 345-369 (2021)
Marginal structural models (MSMs) can be used to estimate the causal effect of a potentially time-varying treatment in the presence of time-dependent confounding via weighted regression. The standard approach of using inverse probability of treatment
Externí odkaz:
https://doaj.org/article/465cea9f35504176bb3c9ec023c5a7cf
Akademický článek
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Publikováno v:
Journal of Causal Inference, Vol 9, Iss 1, Pp 345-369 (2021)
Marginal structural models (MSMs) estimate the causal effect of a time-varying treatment in the presence of time-dependent confounding via weighted regression. The standard approach of using inverse probability of treatment weighting (IPTW) can lead
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8ffe2fa71552680a00f3342e2a3a0685