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\noindent\textbf{Background} Prenatal glucocorticoid exposure alters cardiac development, but whether persistent cardiac effects in childhood follow a dose-response relationship remains unknown. We recently showed that ECG foundation models…

When treating depression, clinicians are interested in determining the optimal treatment for a given patient, which is challenging given the amount of treatments available. To advance individualized treatment allocation, integrating data…

We propose a framework for testing the homogeneity of conditional average treatment effects (CATEs) across multiple experimental and observational studies. Our approach leverages multiple randomized trials to assess whether treatment…

计量经济学 · 经济学 2026-02-25 Ana Armendariz , Martin Huber

Inferring causality using longitudinal observational databases is challenging due to the passive way the data are collected. The majority of associations found within longitudinal observational data are often non-causal and occur due to…

计算工程、金融与科学 · 计算机科学 2016-11-17 Jenna Reps , Uwe Aickelin

Estimating causal effects with propensity scores relies upon the availability of treated and untreated units observed at each value of the estimated propensity score. In settings with strong confounding, limited so-called "overlap" in…

统计方法学 · 统计学 2017-10-25 Corwin M Zigler , Matthew Cefalu

Machine learning strategies like multi-task learning, meta-learning, and transfer learning enable efficient adaptation of machine learning models to specific applications in healthcare, such as prediction of various diseases, by leveraging…

机器学习 · 计算机科学 2024-12-31 Sophie Wharrie , Lisa Eick , Lotta Mäkinen , Andrea Ganna , Samuel Kaski , FinnGen

Subclassification and matching are often used in empirical studies to adjust for observed covariates; however, they are largely restricted to relatively simple study designs with a binary treatment and less developed for designs with a…

统计方法学 · 统计学 2022-01-28 Bo Zhang , Emily J. Mackay , Mike Baiocchi

Existing causal methods for time-varying exposure and time-varying confounding focus on estimating the average causal effect of a time-varying binary treatment on an end-of-study outcome, offering limited tools for characterizing marginal…

统计方法学 · 统计学 2026-01-21 Yu Luo , Kuan Liu , Ramandeep Singh , Daniel J. Graham

Previous studies have suggested a link between alcohol outlets and assaultive violence. In this paper, we explore the effects of alcohol availability on assault crimes at the census tract level over time. The statistical analysis is…

应用统计 · 统计学 2008-02-05 Qingzhao Yu , Bin Li , Richard Scribner , Deborah Cohen

We study identifying and estimating the causal effect of a treatment variable on a long-term outcome using data from an observational and an experimental domain. The observational data are subject to unobserved confounding. Furthermore,…

Life-expectancy is a complex outcome driven by genetic, socio-demographic, environmental and geographic factors. Increasing socio-economic and health disparities in the United States are propagating the longevity-gap, making it a cause for…

应用统计 · 统计学 2018-11-20 Tavpritesh Sethi , Anant Mittal , Shubham Maheshwari , Samarth Chugh

Substance use is a global issue that negatively impacts millions of persons who use drugs (PWUDs). In practice, identifying vulnerable PWUDs for efficient allocation of appropriate resources is challenging due to their complex use patterns…

Mental health issues among college students have reached critical levels, significantly impacting academic performance and overall wellbeing. Predicting and understanding mental health status among college students is challenging due to…

机器学习 · 计算机科学 2025-06-11 Meghna Roy Chowdhury , Wei Xuan , Shreyas Sen , Yixue Zhao , Yi Ding

Stress detection and classification from wearable sensor data is an emerging area of research with significant implications for individuals' physical and mental health. In this work, we introduce a new dataset, ADARP, which contains…

Causal inference on populations embedded in social networks poses technical challenges, since the typical no interference assumption frequently does not hold. Existing methods developed in the context of network interference rely upon the…

统计方法学 · 统计学 2024-04-12 Vanessa McNealis , Erica E. M. Moodie , Nema Dean

Background: Pairwise and network meta-analyses using fixed effect and random effects models are commonly applied to synthesise evidence from randomised controlled trials. The models differ in their assumptions and the interpretation of the…

统计方法学 · 统计学 2017-08-04 Shijie Ren , Jeremy E. Oakley , John W. Stevens

In many observational studies in social science and medicine, subjects or units are connected, and one unit's treatment and attributes may affect another's treatment and outcome, violating the stable unit treatment value assumption (SUTVA)…

统计方法学 · 统计学 2024-06-25 Zhaonan Qu , Ruoxuan Xiong , Jizhou Liu , Guido Imbens

Alzheimer's disease (AD), as a progressive brain disease, affects cognition, memory, and behavior. Similarly, limbic-predominant age-related TDP-43 encephalopathy (LATE) is a recently defined common neurodegenerative disease that mimics the…

计算机与社会 · 计算机科学 2022-09-13 Xinxing Wu , Chong Peng , Peter T. Nelson , Qiang Cheng

In cases of prevalent diseases and disorders, such as Prenatal Alcohol Exposure (PAE), multi-site data collection allows for increased study samples. However, multi-site studies introduce additional variability through heterogeneous…

Background: Many researchers have studied the relationship between diet and health. There are papers showing an association between the consumption of sugar-sweetened beverages and Type 2 diabetes. Many meta-analyses use individual studies…

应用统计 · 统计学 2017-10-09 Karl E. Peace , JingJing Yin , Haresh Rochani , Sarbesh Pandeya , S. Stanley Young