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Creators/Authors contains: "Ouyang, J"

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  1. ; ; (, Journal of Machine Learning Research)
    Statistical inferences for high-dimensional regression models have been extensively studied for their wide applications ranging from genomics, neuroscience, to economics. However, in practice, there are often potential unmeasured confounders associated with both the response and covariates, which can lead to invalidity of standard debiasing methods. This paper focuses on a generalized linear regression framework with hidden confounding and proposes a debiasing approach to address this high-dimensional problem, by adjusting for the effects induced by the unmeasured confounders. We establish consistency and asymp- totic normality for the proposed debiased estimator. The finite sample performance of the proposed method is demonstrated through extensive numerical studies and an application to a genetic data set. 
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    Accepted Manuscript Full Text Available
  2. ; ; ; ; (, American Society for Engineering Education)
    Team-based learning is commonly used in engineering introductory courses. As students of a team may be from vastly different backgrounds, academically and non-academically, it is important for faculty members to know what aid or hinder team success. The dataset that is used in this paper includes student personality inputs, self-and-peer-assessments of teamwork, and perceptions of teamwork outcomes. Using this information, we developed several bayesian models that are able to predict if a team is working well. We also constructed and estimated Q-matrices which are crucial in explaining the relationship between latent traits and students’ characteristics in cognitive diagnostic models. The prediction and diagnostic models are able to help faculty members and instructors to gain insights into finding ways to separate students into teams more effectively so that students have a positive team-based learning experience. 
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    Accepted Manuscript Full Text Available
  3. ; ; ; (, Journal of machine learning research)
    Accepted Manuscript Full Text Available