7 papers
Surrogate Assisted Semi-supervised Inference for High Dimensional Risk Prediction
Jue Hou, Zijian Guo, Tianxi Cai
Risk modeling with EHR data is challenging due to a lack of direct observations on the disease outcome, and the high dimensionality of the candidate predictors. In this paper, we d…
Inference for the Case Probability in High-dimensional Logistic Regression
Zijian Guo, Prabrisha Rakshit, Daniel S. Herman +1
Labeling patients in electronic health records with respect to their statuses of having a disease or condition, i.e. case or control statuses, has increasingly relied on prediction…
Group Inference in High Dimensions with Applications to Hierarchical Testing
Zijian Guo, Claude Renaux, Peter Bühlmann +1
High-dimensional group inference is an essential part of statistical methods for analysing complex data sets, including hierarchical testing, tests of interaction, detection of het…
Extreme Eigenvalues of Nonlinear Correlation Matrices with Applications to Additive Models
Zijian Guo, Cun-Hui Zhang
The maximum correlation of functions of a pair of random variables is an important measure of stochastic dependence. It is known that this maximum nonlinear correlation is identica…
Optimal Statistical Inference for Individualized Treatment Effects in High-dimensional Models
Tianxi Cai, Tony Cai, Zijian Guo
The ability to predict individualized treatment effects (ITEs) based on a given patient's profile is essential for personalized medicine. We propose a hypothesis testing approach t…
Semi-supervised Inference for Explained Variance in High-dimensional Linear Regression and Its Applications
T. Tony Cai, Zijian Guo
This paper considers statistical inference for the explained variance under the high-dimensional linear model in the semi-supervised setting, where i…