Survival analysis under complex sampling; quantile regression; treatment of censored covariates; biomarker evaluation and risk prediction; semiparametric and nonparametric inferences; analytic methods for high-dimensional data
715 North Pleasant Street
Amherst, MA 01003
Jing Qian’s research interests include survival analysis under complex sampling, in which he develops estimation and hypothesis testing methods under censoring and dependent truncation arising from observational studies. By developing quantile regression approach for time-to-event outcomes under complex sampling design, Qian introduces flexible modeling methods to deal with non-constant biomarker effects in cancer epidemiological studies. Currently, he is also active in developing statistical methods for covariates subject to censoring, risk prediction under complex sampling design, high-dimensional variable selection, and prediction for large-scale imaging or genetic biomarkers.
Qian’s main areas of collaborative research include Alzheimer's disease studies and cancer epidemiology.