Results 31 to 40 of about 158,058 (264)

A clarification on the links between potential outcomes and do-interventions

open access: yesJournal of Causal Inference
Most of the scientific literature on causal modeling considers the structural framework of Pearl and the potential-outcome framework of Rubin to be formally equivalent and therefore interchangeably uses do-interventions and the potential-outcome ...
De Lara Lucas
doaj   +1 more source

Standardizing Structural Causal Models

open access: yesCoRR
Synthetic datasets generated by structural causal models (SCMs) are commonly used for benchmarking causal structure learning algorithms. However, the variances and pairwise correlations in SCM data tend to increase along the causal ordering. Several popular algorithms exploit these artifacts, possibly leading to conclusions that do not generalize to ...
Weronika Ormaniec   +4 more
openaire   +3 more sources

Reducing Causality to Functions with Structural Models

open access: yesCoRR, 2023
47 pages, submitted to The British Journal for the Philosophy of ...
openaire   +2 more sources

Health‐Related Social Needs in Children With Sickle Cell Disease Are Associated With Worse Health‐Related Quality of Life

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Children with sickle cell disease (SCD) face multiple acute and chronic medical complications that may impact their quality of life as reported by patients themselves. Health‐related social needs (HRSNs), such as food and housing insecurity, are common in people with SCD, but the association between HRSNs and patient‐reported ...
Sarah J. Marks   +5 more
wiley   +1 more source

A practical method to control spatiotemporal confounding in environmental impact studies

open access: yesMethodsX, 2018
Separating natural spatiotemporal variation from the impact of human activities has long been a challenge in environmental impact studies. To overcome this problem, a causal modelling method based on spatiotemporal data, integrated with existing ...
Rezvan Hatami
doaj   +1 more source

A Linear “Microscope” for Interventions and Counterfactuals

open access: yesJournal of Causal Inference, 2017
This note illustrates, using simple examples, how causal questions of non-trivial character can be represented, analyzed and solved using linear analysis and path diagrams.
Pearl Judea
doaj   +1 more source

Feasibility and Safety of Somato‐Cognitive Coordination Therapy for Cerebellar Ataxia Following Pediatric Brain Tumor Treatment

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Cerebellar ataxia after pediatric brain tumor treatment can cause persistent gait, balance, and speech impairment, yet no established rehabilitation strategy exists. Somato‐cognitive coordination therapy (SCCT) is a virtual reality–guided intervention designed to promote sensorimotor integration through visually constrained reaching
Masanobu Takeuchi   +10 more
wiley   +1 more source

Early Impact of Childhood Opportunity on Neurocognitive Outcomes in Sickle Cell Disease

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Introduction Neurocognitive impairment is a well‐recognized complication of sickle cell disease (SCD) that begins early in childhood and persists across development. While cerebrovascular injury contributes substantially to risk, neurocognitive deficits are also observed in children without overt or silent cerebral infarctions, suggesting ...
Julia E. LaMotte   +5 more
wiley   +1 more source

Incidence and Severity of Carboplatin‐Associated Hearing Loss in Children With Cancer Assessed by the SIOP Boston 2012 Ototoxicity Criteria

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Platinum‐based chemotherapy is known to cause severe and debilitating hearing loss, but unlike cisplatin, the true incidence of carboplatin‐induced hearing loss remains unclear. We evaluated functional hearing outcomes in children receiving carboplatin to determine the incidence and severity of ototoxicity. Procedure We identified a
Aniket Chawla   +6 more
wiley   +1 more source

Learning Causal Abstractions of Linear Structural Causal Models

open access: yesCoRR
The need for modelling causal knowledge at different levels of granularity arises in several settings. Causal Abstraction provides a framework for formalizing this problem by relating two Structural Causal Models at different levels of detail. Despite increasing interest in applying causal abstraction, e.g.
Massidda, Riccardo   +2 more
openaire   +5 more sources

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