55 citations · 98 across the 7 of their papers we have counts for
7 papers
An integrative sparse boosting analysis of cancer genomic commonality and difference
Yifan Sun, Zhengyang Sun, Yu Jiang +2
In cancer research, high-throughput profiling has been extensively conducted. In recent studies, the integrative analysis of data on multiple cancer patient groups/subgroups has be…
Identification of cancer omics commonality and difference via community fusion
Yifan Sun, Yu Jiang, Yang Li +1
The analysis of cancer omics data is a "classic" problem, however, still remains challenging. Advancing from early studies that are mostly focused on a single type of cancer, some…
Semiparametric integrative interaction analysis for non-small-cell lung cancer
Yang Li, Fan Wang, Rong Li +1
In the genomic analysis, it is significant while challenging to identify markers associated with cancer outcomes or phenotypes. Based on the biological mechanisms of cancers and th…
Optimal integrating learning for split questionnaire design type data
Cunjie Lin, Jingfu Peng, Yichen Qin +2
In the era of data science, it is common to encounter data with different subsets of variables obtained for different cases. An example is the split questionnaire design (SQD), whi…
Testing for Treatment Effect in Covariate-Adaptive Randomized Clinical Trials with Generalized Linear Models and Omitted Covariates
Li Yang, Wei Ma, Yichen Qin +1
Concerns have been expressed over the validity of statistical inference under covariate-adaptive randomization despite the extensive use in clinical trials. In the literature, the…
Statistical Inference for Covariate-Adaptive Randomization Procedures
Wei Ma, Yichen Qin, Yang Li +1
Covariate-adaptive randomization (CAR) procedures are frequently used in comparative studies to increase the covariate balance across treatment groups. However, because randomizati…
Variable Selection with Scalable Bootstrap in Generalized Linear Model for Massive Data
Zhibing He, Yichen Qin, Ben-Chang Shia +1
Bootstrap is commonly used as a tool for non-parametric statistical inference to estimate meaningful parameters in Variable Selection Models. However, for massive dataset that has…