causalinference相关论文
The era of big data brings opportunities and challenges to developing new statistical methods and models to evaluate soc......
For time-to-event outcome of multiple treatment groups,the Kaplan-Meier estimator is often used to estimate survival fun......
Large administrative data from healthcare claims and electronic health records provide significant opportunities for hea......
Beyond the obvious use of large scale RCT data to establish a treatment effect the same data can be used to understand/d......
Unlike randomized trial,statistical strategies for inferring the unbiased causal relationship are required in the observ......
Propensity score matching is widely used in various research fields to adjust for measured confounders in observational ......
Despite the existing well-developed statistical methods for mediation analysis,applied researchers are still faced with ......
Smart causal machine learner that combines CT image and RNA-seq markers for cancer diagnosis and pre
The current paradigm for disease risk prediction and association analysis is to use unstructured variables for classific......
Over the past decade,double-robust(DR)estimators have been proposed for a variety of target parameters in causal inferen......
We study variable selection problem in causal inference.This is different from the regular variable selection problem su......
In this talk,I will introduce a motivating example of studying the causal mechanisms for the effect of socioeconomic ine......
This article introduces a new randomization procedure to improve the covariate balance across treatment groups.Covariate......
While the use of real world/observational/big data for comparative effectiveness analyses has grown in recent years,caus......
Most powerful statistics for RNA-seq and image association analysis and its application to kidney ca
The structure of biomedical images of the tissue of human body is strongly shaped by the genetic and expression variatio......
Deep learning in multi-level causal genomic-epigenomic network analysis and its application to Alzhe
The next generation of genomic,sensing and image technologies and the precision medicine project will produce deeper and......
Causal inference practitioners are routinely presented with the challenge of wanting to adjust for large numbers of cova......
Inferring a causal relationship is an important task in both social science and health research.In an observational stud......
No unmeasured and correctly modelled effect modifiers - implications for confounding control in caus
Confounding and effect modification are both central,yet often strictly distinguished concepts in epidemiology [Miettine......
不良饮食是慢性非传染性疾病最重要的可控危险因素之一，但通过随机对照试验定量阐明具体饮食因素与健康结局的因果关联面临很多困难......
