Results 1 to 10 of about 414,150 (267)

Probabilistic Matching: Causal Inference under Measurement Errors [PDF]

, 2017
The abundance of data produced daily from large variety of sources has boosted the need of novel approaches on causal inference analysis from observational data. Observational data often contain noisy or missing entries.
Musolesi, Mirco, Tino, Peter, Tsapeli, Fani   +2 more
core   +2 more sources

Multisensory causal inference in the brain [PDF]

, 2015
At any given moment, our brain processes multiple inputs from its different sensory modalities (vision, hearing, touch, etc.). In deciphering this array of sensory information, the brain has to solve two problems: (1) which of the inputs originate from ...
A Pouget, BE Stein, BE Stein, C Dahl, C Kayser, C Kayser, CE Schroeder, Christoph Kayser, CR Fetsch, D Kersten, D Talsma, DE Angelaki, DR Wozny, E Payzan-LeNestour, G Hatfield, JV Haxby, KP Kording, L Shams, L Shams, L Shams, Ladan Shams, M Rigotti, MO Ernst, MO Ernst, MO Ernst, MT Wallace, NW Roach, S Shamma, SW Lee, T Rohe, UR Beierholm, WJ Ma   +31 more
core   +4 more sources

FAST RESTRICTED CAUSAL INFERENCE [PDF]

Demonstratio Mathematica, 2000
Hidden variables are well known sources of disturbance when recovering belief networks from data based only on measurable variables. Hence models assuming existence of hidden variables are under development. This paper presents a new algorithm "accelerating" the known CI algorithm of Spirtes, Glymour and Scheines {Spirtes:93}.
openaire   +3 more sources

Causal graphical models in systems genetics: A unified framework for joint inference of causal network and genetic architecture for correlated phenotypes [PDF]

, 2009
Causal inference approaches in systems genetics exploit quantitative trait loci (QTL) genotypes to infer causal relationships among phenotypes. The genetic architecture of each phenotype may be complex, and poorly estimated genetic architectures may ...
Attie, Alan D., Keller, Mark P., Neto, Elias Chaibub, Yandell, Brian S.   +3 more
core   +3 more sources

Polydesigns and Causal Inference

Biometrics, 2005
Summary In an increasingly common class of studies, the goal is to evaluate causal effects of treatments that are only partially controlled by the investigator. In such studies there are two conflicting features: (1) a model on the full cohort design and data can identify the causal effects of interest, but can be sensitive to extreme regions of that ...
Li, Fan, Frangakis, Constantine E.
openaire   +4 more sources

MERLiN: Mixture Effect Recovery in Linear Networks [PDF]

, 2015
Causal inference concerns the identification of cause-effect relationships between variables, e.g. establishing whether a stimulus affects activity in a certain brain region.
Gretton, Arthur, Grosse-Wentrup, Moritz, Weichwald, Sebastian   +2 more
core   +2 more sources

Clarifying causal mediation analysis for the applied researcher: Defining effects based on what we want to learn

, 2020
The incorporation of causal inference in mediation analysis has led to theoretical and methodological advancements -- effect definitions with causal interpretation, clarification of assumptions required for effect identification, and an expanding array ...
Nguyen, Trang Quynh, Schmid, Ian, Stuart, Elizabeth A.   +2 more
core   +1 more source

Causal inference

Revista de la Facultad de Ciencias de la Salud, 2014
Establishing causality has been a problem throughout history of philosophy of science. This paper discusses the philosophy of causal inference along the different school of thoughts and methods: Rationalism, Empiricism, Inductive method, Hypothetical ...
Richard Shoemaker
doaj   +2 more sources

Semiparametric theory and empirical processes in causal inference

, 2016
In this paper we review important aspects of semiparametric theory and empirical processes that arise in causal inference problems. We begin with a brief introduction to the general problem of causal inference, and go on to discuss estimation and ...
A. Belloni, A. Belloni, A.A. Tsiatis, A.R. Luedtke, A.W. Vaart van der, A.W. Vaart van der, A.W. Vaart van der, A.W. Vaart van der, B. Chakraborty, C.F. Manski, D. Pollard, D. Pollard, D.B. Rubin, D.B. Rubin, D.W.K. Andrews, D.W.K. Andrews, E. Tchetgen, E. Tchetgen, E. Tchetgen, E.H. Kennedy, E.L. Ogburn, G.R. Shorack, I. Diaz, I. Diaz, J. Hahn, J. Pearl, J. Pearl, J. Pfanzagl, J. Pfanzagl, J.D. Angrist, J.L. Horowitz, J.M. Begun, J.M. Robins, J.M. Robins, J.M. Robins, J.M. Robins, J.M. Robins, J.M. Robins, L.A. Stefanski, M. Carone, M.A. Hernan, M.G. Hudgens, M.J. Laan van der, M.J. Laan van der, M.J. Laan van der, M.J. Laan van der, M.J. Laan van der, M.J. Laan van der, M.J. Laan van der, M.J. Laan van der, M.L. Petersen, M.R. Kosorok, P.A. Dawid, P.J. Bickel, R. Neugebauer, R.D. Gill, S. Rose, S.A. Murphy, T.J. VanderWeele, T.J. VanderWeele, T.J. VanderWeele, T.J. VanderWeele, W. Zheng, W.K. Newey, W.K. Newey   +64 more
core   +1 more source

Adverse events associated with COVID-19 vaccination or diagnosis among pregnant and non-pregnant women in the United States, 2021-2022

International Journal of Infectious Diseases
Objectives: To quantify the incidence of adverse events after COVID-19 vaccination and COVID-19 diagnosis in women of reproductive age; to examine pregnancy as a potential risk modifier.
Stacey L. Rowe, Sheena G. Sullivan, Julia J. Koerber, Flor M. Muñoz, Matthew M. Coates, Onyebuchi A. Arah, Annette K. Regan   +6 more
doaj   +1 more source