Zobrazeno 1 - 10
of 593
pro vyhledávání: '"Cui Yifan"'
There is a fast-growing literature on estimating optimal treatment rules directly by maximizing the expected outcome. In biomedical studies and operations applications, censored survival outcome is frequently observed, in which case the restricted me
Externí odkaz:
http://arxiv.org/abs/2408.09155
Breast cancer patients may experience relapse or death after surgery during the follow-up period, leading to dependent censoring of relapse. This phenomenon, known as semi-competing risk, imposes challenges in analyzing treatment effects on breast ca
Externí odkaz:
http://arxiv.org/abs/2407.01770
R. A. Fisher introduced the concept of fiducial as a potential replacement for the Bayesian posterior distribution in the 1930s. During the past century, fiducial approaches have been explored in various parametric and nonparametric settings. However
Externí odkaz:
http://arxiv.org/abs/2404.18779
Autor:
Cui, Yifan, Han, Sukjin
In this paper, we explore optimal treatment allocation policies that target distributional welfare. Most literature on treatment choice has considered utilitarian welfare based on the conditional average treatment effect (ATE). While average welfare
Externí odkaz:
http://arxiv.org/abs/2311.15878
Autor:
Zhao, Pan, Cui, Yifan
Recently, there has been a surge in methodological development for the difference-in-differences (DiD) approach to evaluate causal effects. Standard methods in the literature rely on the parallel trends assumption to identify the average treatment ef
Externí odkaz:
http://arxiv.org/abs/2310.09545
Autor:
Sverdrup, Erik, Cui, Yifan
Efficiently and flexibly estimating treatment effect heterogeneity is an important task in a wide variety of settings ranging from medicine to marketing, and there are a considerable number of promising conditional average treatment effect estimators
Externí odkaz:
http://arxiv.org/abs/2301.10913
Characterizing the sleep-wake cycle in adolescents is an important prerequisite to better understand the association of abnormal sleep patterns with subsequent clinical and behavioral outcomes. The aim of this research was to develop hidden Markov mo
Externí odkaz:
http://arxiv.org/abs/2212.11224
Autor:
Shen, Tao, Cui, Yifan
A common concern when a policymaker draws causal inferences from and makes decisions based on observational data is that the measured covariates are insufficiently rich to account for all sources of confounding, i.e., the standard no confoundedness a
Externí odkaz:
http://arxiv.org/abs/2212.09494
Autor:
Cui, Yifan, Hannig, Jan
Inferential models have recently gained in popularity for valid uncertainty quantification. In this paper, we investigate inferential models by exploring relationships between inferential models, fiducial inference, and confidence curves. In short, w
Externí odkaz:
http://arxiv.org/abs/2205.05612
Contrasting marginal counterfactual survival curves across treatment arms is an effective and popular approach for inferring the causal effect of an intervention on a right-censored time-to-event outcome. A key challenge to drawing such inferences in
Externí odkaz:
http://arxiv.org/abs/2204.13144