Results 61 to 70 of about 133,258 (310)
The variance of causal effect estimators for binary v-structures
Journal of Causal Inference, 2022 Adjusting for covariates is a well-established method to estimate the total causal effect of an exposure variable on an outcome of interest. Depending on the causal structure of the mechanism under study, there may be different adjustment sets, equally ...
Kuipers Jack, Moffa Giusi
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background An earlier study on children diagnosed with acute lymphoblastic leukemia (ALL) at Moi Teaching and Referral Hospital (MTRH) in Kenya reported a low event‐free survival (EFS), excess treatment abandonment, and high induction mortality.
Gilbert Olbara +7 more
wiley +1 more source
Causal reasoning and meta learning using kernel mean embeddings [PDF]
, 2023 Kernel methods have been an essential instrument in machine learning over the years due to their ability to map data into high dimensional spaces efficiently.
Ton, Jean-Francois
core +2 more sources
Sufficient Causes: On Oxygen, Matches, and Fires
Journal of Causal Inference, 2019 We demonstrate how counterfactuals can be used to compute the probability that one event was/is a sufficient cause of another, and how counterfactuals emerge organically from basic scientific knowledge, rather than manipulative experiments.
Pearl Judea
doaj +1 more source
Journal of Causal Inference, 2022 Recent studies have indicated that it is possible to protect individuals from HIV infection using passive infusion of monoclonal antibodies. However, in order for monoclonal antibodies to confer robust protection, the antibodies must be capable of ...
Jin Yutong, Benkeser David
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Neurotoxicity is a rare, often dose‐limiting adverse effect of methotrexate (MTX) therapy that disproportionally affects Latino children. Factors contributing to the observed disparity are not well understood. This study leveraged admixture mapping to identify genetic regions associated with MTX‐related neurotoxicity susceptibility ...
Rachel D. Harris +24 more
wiley +1 more source
Decision-theoretic foundations for statistical causality
Journal of Causal Inference, 2021 We develop a mathematical and interpretative foundation for the enterprise of decision-theoretic (DT) statistical causality, which is a straightforward way of representing and addressing causal questions.
Dawid Philip
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Pediatric supportive care clinical trials often involve multiple clinically important outcomes, complicating trial interpretation. Hierarchical composite endpoints (HCEs) provide a framework to integrate key outcomes according to clinical importance.
Willem H. Collier +11 more
wiley +1 more source
Nonparametric inference for interventional effects with multiple mediators
Journal of Causal Inference, 2021 Understanding the pathways whereby an intervention has an effect on an outcome is a common scientific goal. A rich body of literature provides various decompositions of the total intervention effect into pathway-specific effects.
Benkeser David, Ran Jialu
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Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Maintenance hemodialysis (MHD) patients frequently suffer from frailty, characterized by reduced physical function and poor prognosis. Myokines, such as myonectin, secreted by muscle, are emerging regulators of systemic health. This study investigated the relationship between serum myonectin, adipokines (adiponectin, omentin), and ...
Kenichi Kono +7 more
wiley +1 more source