Gene expression-based heterogeneity analysis has been extensively conduc...
The quantile varying coefficient (VC) model can flexibly capture dynamic...
Functional data analysis has been extensively conducted. In this study, ...
Heterogeneity is a hallmark of many complex diseases. There are multiple...
In diverse fields ranging from finance to omics, it is increasingly comm...
If error distribution has heteroscedasticity, it voliates the assumption...
Epidemiologic studies and clinical trials with a survival outcome are of...
Genetic interactions play an important role in the progression of comple...
Penalized variable selection for high dimensional longitudinal data has
...
Increasing evidence has shown that gene-gene interactions have important...
Gene-environment (G×E) interactions have important implications to
eluci...
For most if not all cancers, prognosis is of significant importance, and...
Partial least squares, as a dimension reduction method, has become
incre...
Gene-environment interactions have important implications to elucidate t...
For complex diseases, beyond the main effects of genetic (G) and
environ...
For the outcomes and phenotypes of complex diseases, multiple types of
m...
We treat the problem of testing for association between a functional var...
Many complex diseases are known to be affected by the interactions betwe...
The identification of predictive biomarkers from a large scale of covari...
For the etiology, progression, and treatment of complex diseases,
gene-e...
For all diseases, prevalence has been carefully studied. In the "classic...
Measurement error is an important problem that has not been very well st...