Results 71 to 80 of about 96,494 (250)

Confounding Equivalence in Causal Inference

open access: yesJournal of Causal Inference, 2014
The paper provides a simple test for deciding, from a given causal diagram, whether two sets of variables have the same bias-reducing potential under adjustment.
Pearl Judea, Paz Azaria
doaj   +1 more source

Systemic dysregulation of apolipoproteins in amyotrophic lateral sclerosis serum

open access: yesFEBS Open Bio, EarlyView.
Amyotrophic lateral sclerosis (ALS) is a fatal disease that damages motor neurons. This study found that people with ALS show significant changes in blood fats and the proteins that carry them. Several apolipoproteins were higher, lipid balances were altered, and normal protein–lipid relationships were disrupted.
Finula I. Isik   +6 more
wiley   +1 more source

A Conditional Randomization Test to Account for Covariate Imbalance in Randomized Experiments

open access: yesJournal of Causal Inference, 2016
We consider the conditional randomization test as a way to account for covariate imbalance in randomized experiments. The test accounts for covariate imbalance by comparing the observed test statistic to the null distribution of the test statistic ...
Hennessy Jonathan   +4 more
doaj   +1 more source

Predicting and Comparing the Subjective Health Experience of Older Cancer Survivors and Non‐Cancer Survivors: A Modeling Approach

open access: yesAging and Cancer, EarlyView.
This study underscores the significant influence of frailty and vitality on the subjective health experience of older cancer survivors with acceptance and control emerging as salient mediators. These findings affirm the conceptual and empirical robustness of the model highlighting its potential utility in shaping future interventions for older cancer ...
Damien S. E. Broekharst   +4 more
wiley   +1 more source

Invariant Causal Prediction for Nonlinear Models

open access: yesJournal of Causal Inference, 2018
An important problem in many domains is to predict how a system will respond to interventions. This task is inherently linked to estimating the system’s underlying causal structure.
Heinze-Deml Christina   +2 more
doaj   +1 more source

Re‐Awakening Public Attention to the Silent Pandemic of Cancer Among Older Adults in Low‐ and Middle‐Income Countries

open access: yesAging and Cancer, EarlyView.
ABSTRACT As global populations age, cancer is increasingly becoming a leading cause of morbidity and mortality among older adults, particularly in low‐ and middle‐income countries (LMICs). Despite accounting for the majority of new cancer cases and deaths, older individuals remain underrepresented in cancer research, clinical guidelines, and health ...
Ibrahim Bidemi Abdullateef   +2 more
wiley   +1 more source

From urn models to box models: Making Neyman's (1923) insights accessible

open access: yesJournal of Causal Inference
Neyman’s 1923 paper introduced the potential outcomes framework and the foundations of randomization-based inference. We discuss the influence of Neyman’s paper on four introductory to intermediate-level textbooks by Berkeley faculty members (Scheffé ...
Lin Winston   +3 more
doaj   +1 more source

Approximate Kernel-Based Conditional Independence Tests for Fast Non-Parametric Causal Discovery

open access: yesJournal of Causal Inference, 2019
Constraint-based causal discovery (CCD) algorithms require fast and accurate conditional independence (CI) testing. The Kernel Conditional Independence Test (KCIT) is currently one of the most popular CI tests in the non-parametric setting, but many ...
Strobl Eric V.   +2 more
doaj   +1 more source

Tracking Motor Progression and Device‐Aided Therapy Eligibility in Parkinson's Disease

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To characterise the progression of motor symptoms and identify eligibility for device‐aided therapies in Parkinson's disease, using both the 5‐2‐1 criteria and a refined clinical definition, while examining differences across genetic subgroups.
David Ledingham   +7 more
wiley   +1 more source

Conditional generative adversarial networks for individualized causal mediation analysis

open access: yesJournal of Causal Inference
Most classical methods popularly used in causal mediation analysis can only estimate the average causal effects and are difficult to apply to precision medicine.
Huan Cheng, Sun Rongqian, Song Xinyuan
doaj   +1 more source

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