목록Research (6)
Outcome : ScalarMediator : FunctionTreatment : Scalar https://pmc.ncbi.nlm.nih.gov/articles/PMC4112546/ Functional Causal Mediation Analysis With an Application to Brain Connectivity - PMCAbstract Mediation analysis is often used in the behavioral sciences to investigate the role of intermediate variables that lie on the causal path between a randomized treatment and an outcome variable. Typic..
https://gpapadogeorgou.netlify.app/files/HD_DR.pdf Abstract목적 : treatment와 outcome모델에 대한 Posterior distribution이 doubly robust estimators와 어떻게 함께 사용될 수 있는지를 보여주는 것. treatment와 outcome을 플렉서블한 프레임워크로 모델링 할건데 여기서 베이지안 방법을 사용. 베이지안 방법을 통해 모델의존도를 줄이고 nonlinearity를 적용시킬수 있고 covariate space에 대한 차원축소가 가능하기 때문에. We show how posterior distributions of treat- ment and outcome models can be used together ..
Bayesian nonparametric modeling for causal inference.
1. Context of the Problem (Causal Inference in Nonexperimental Settings)Researchers face challenges when trying to identify causal effects without experimental data, where treatment assignment is not random.Many causal inference methods assume "ignorability" (that the treatment assignment is independent of the outcomes, conditional on observed covariates). These methods typically require the res..
BART : Bayesian additive regression trees
https://projecteuclid.org/journals/annals-of-applied-statistics/volume-4/issue-1/BART-Bayesian-additive-regression-trees/10.1214/09-AOAS285.full BART: Bayesian additive regression treesWe develop a Bayesian “sum-of-trees” model where each tree is constrained by a regularization prior to be a weak learner, and fitting and inference are accomplished via an iterative Bayesian backfitting MCMC algor..
