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pro vyhledávání: '"Hernan Miguel"'
The g-formula can be used to estimate causal effects of sustained treatment strategies using observational data under the identifying assumptions of consistency, positivity, and exchangeability. The non-iterative conditional expectation (NICE) estima
Externí odkaz:
http://arxiv.org/abs/2410.21531
In randomized trials, the per-protocol effect, that is, the effect of being assigned a treatment strategy and receiving treatment according to the assigned strategy, is sometimes thought to reflect the effect of the treatment strategy itself, without
Externí odkaz:
http://arxiv.org/abs/2408.14710
There is increasing interest in combining information from experimental studies, including randomized and single-group trials, with information from external experimental or observational data sources. Such efforts are usually motivated by the desire
Externí odkaz:
http://arxiv.org/abs/2406.03302
Autor:
VanderWeele Tyler J., Hernan Miguel A.
Publikováno v:
Journal of Causal Inference, Vol 1, Iss 1, Pp 1-20 (2013)
Abstract: In this article, we discuss causal inference when there are multiple versions of treatment. The potential outcomes framework, as articulated by Rubin, makes an assumption of no multiple versions of treatment, and here we discuss an extensio
Externí odkaz:
https://doaj.org/article/8040265765634755b965a436509c0165
Autor:
Hernan Miguel
Publikováno v:
Epistemología e Historia de la Ciencia, Vol 1, Iss 1 (2016)
Se suele aceptar que no es posible garantizar la simetría de la relación de similaridad comparativa global entre mundos posibles. Sin embargo, existen usos exitosos y tentadores al suponer casos simétricos que pueden dar lugar a pensar que la falt
Externí odkaz:
https://doaj.org/article/ffe66041cd044010b567638d3f3e68dc
We discuss the identifiability of causal estimands for generalizability and transportability analyses, both under perfect and imperfect adherence to treatment assignment. We consider a setting where the trial data contain information on baseline cova
Externí odkaz:
http://arxiv.org/abs/2211.04876
Autor:
Dahabreh, Issa J., Robins, James M., Haneuse, Sebastien J-P. A., Robertson, Sarah E., Steingrimsson, Jon A., Hernán, Miguel A.
When individuals participating in a randomized trial differ with respect to the distribution of effect modifiers compared compared with the target population where the trial results will be used, treatment effect estimates from the trial may not dire
Externí odkaz:
http://arxiv.org/abs/2207.09982
Autor:
Fornés Nélida Schmid, Martins Ignez Salas, Hernan Miguel, Velásquez-Meléndez Gustavo, Ascherio Alberto
Publikováno v:
Revista de Saúde Pública, Vol 34, Iss 4, Pp 380-387 (2000)
OBJECTIVE: To identify the association between food group consumption frequency and serum lipoprotein levels among adults. METHODS: The observations were made during a cross-sectional survey of a representative sample of men and women over 20 years o
Externí odkaz:
https://doaj.org/article/75c0fcd0414f4234bd1603e872f692f6
A randomized trial and an analysis of observational data designed to emulate the trial sample observations separately, but have the same eligibility criteria, collect information on some shared baseline covariates, and compare the effects of the same
Externí odkaz:
http://arxiv.org/abs/2203.14857
Publikováno v:
Epidemiology 33 (2022) 114-120
The parametric g-formula is an approach to estimating causal effects of sustained treatment strategies from observational data. An often cited limitation of the parametric g-formula is the g-null paradox: a phenomenon in which model misspecification
Externí odkaz:
http://arxiv.org/abs/2103.03857