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pro vyhledávání: '"Chan, Kwun Chuen Gary"'
As advancements in novel biomarker-based algorithms and models accelerate disease risk prediction and stratification in medicine, it is crucial to evaluate these models within the context of their intended clinical application. Prediction models outp
Externí odkaz:
http://arxiv.org/abs/2408.01626
Covariate balancing methods have been widely applied to single or monotone missing patterns and have certain advantages over likelihood-based methods and inverse probability weighting approaches based on standard logistic regression. In this paper, w
Externí odkaz:
http://arxiv.org/abs/2402.08873
We study treatment effect estimation with functional treatments where the average potential outcome functional is a function of functions, in contrast to continuous treatment effect estimation where the target is a function of real numbers. By consid
Externí odkaz:
http://arxiv.org/abs/2309.08039
In this article, we propose a new class of consistent tests for $p$-variate normality. These tests are based on the characterization of the standard multivariate normal distribution, that the Hessian of the corresponding cumulant generating function
Externí odkaz:
http://arxiv.org/abs/2303.11388
A variety of statistics based on sample spacings has been studied in the literature for testing goodness-of-fit to parametric distributions. To test the goodness-of-fit to a nonparametric class of univariate shape-constrained densities, including wid
Externí odkaz:
http://arxiv.org/abs/2211.13272
Data harmonization is the process by which an equivalence is developed between two variables measuring a common trait. Our problem is motivated by dementia research in which multiple tests are used in practice to measure the same underlying cognitive
Externí odkaz:
http://arxiv.org/abs/2110.06077
In this paper, we propose a novel method for matrix completion under general non-uniform missing structures. By controlling an upper bound of a novel balancing error, we construct weights that can actively adjust for the non-uniformity in the empiric
Externí odkaz:
http://arxiv.org/abs/2106.05850
We study nonparametric estimation for the partially conditional average treatment effect, defined as the treatment effect function over an interested subset of confounders. We propose a hybrid kernel weighting estimator where the weights aim to contr
Externí odkaz:
http://arxiv.org/abs/2103.03437
In many medical studies, an ultimate failure event such as death is likely to be affected by the occurrence and timing of other intermediate clinical events. Both event times are subject to censoring by loss-to-follow-up but the nonterminal event may
Externí odkaz:
http://arxiv.org/abs/2010.00061
Autor:
Xie, Yuxiang, Chan, Kwun Chuen Gary
Variable selection has been widely used in data analysis for the past decades, and it becomes increasingly important in the Big Data era as there are usually hundreds of variables available in a dataset. To enhance interpretability of a model, identi
Externí odkaz:
http://arxiv.org/abs/1807.00931