Zobrazeno 1 - 10
of 90
pro vyhledávání: '"Andrea Rotnitzky"'
Autor:
Andrea Rotnitzky
Publikováno v:
Harvard Data Science Review, Vol 5, Iss 2 (2023)
Externí odkaz:
https://doaj.org/article/dc04f1787c9a4e689e0174ce6a96c370
Publikováno v:
Biometrika. 109:49-65
We study the selection of covariate adjustment sets for estimating the value of point exposure dynamic policies, also known as dynamic treatment regimes, assuming a non-parametric causal graphical model with hidden variables, in which at least one ad
We study efficient estimation of an interventional mean associated with a point exposure treatment under a causal graphical model represented by a directed acyclic graph without hidden variables. Under such a model, it may happen that a subset of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2c8faa6b9117619f67ed2910d0f14027
Autor:
Ezequiel Smucler, Andrea Rotnitzky
We study the selection of adjustment sets for estimating the interventional mean under an individualized treatment rule. We assume a non-parametric causal graphical model with, possibly, hidden variables and at least one adjustment set composed of ob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::012631c0ecf0cf10b4cfc3781517f132
We derive new estimators of an optimal joint testing and treatment regime under the no direct effect (NDE) assumption that a given laboratory, diagnostic, or screening test has no effect on a patient's clinical outcomes except through the effect of t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32c1126edaef40f3fd89374ca5226879
Publikováno v:
Biometrika
CONICET Digital (CONICET)
Consejo Nacional de Investigaciones Científicas y Técnicas
instacron:CONICET
CONICET Digital (CONICET)
Consejo Nacional de Investigaciones Científicas y Técnicas
instacron:CONICET
We consider inference under a nonparametric or semiparametric model with likelihood that factorizes as the product of two or more variation-independent factors.We are interested in a finitedimensional parameter that depends on only one of the likelih
In this article we study a class of parameters with the so-called `mixed bias property'. For parameters with this property, the bias of the semiparametric efficient one step estimator is equal to the mean of the product of the estimation errors of tw
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd5f70d6a6b217f5715ff64e36c85ebf
http://arxiv.org/abs/1904.03725
http://arxiv.org/abs/1904.03725
We consider estimation, from longitudinal observational data, of the parameters of marginal structural mean models for unconstrained outcomes. Current proposals include inverse probability of treatment weighted and double robust (DR) estimators. A di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c7a2306b0c7b8a6e732557ea91e2af3d
Wiley Online Library
Wiley Online Library
Autor:
Sebastian Haneuse, Andrea Rotnitzky
Publikováno v:
Statistics in Medicine. 32:5260-5277
Motivated by a study of surgical operating time and post-operative outcomes for lung cancer, we consider the estimation of causal effects of continuous point-exposure treatments. To investigate causality, the standard paradigm postulates a series of
Publikováno v:
Biometrika. 99(2):439-456
Recently proposed double-robust estimators for a population mean from incomplete data and for a finite number of counterfactual means can have much higher efficiency than the usual double-robust estimators under misspecification of the outcome model.