Dr. Qixuan Chen has primary research interest in the analysis of complex survey data and data with missing values. Her research on survey sampling focuses on Bayesian model-based methods that include sample weights as covariates in the model. Her research on missing data focuses on multiple imputation and survey nonresponse. Dr. Chen is also interested in the novel application of Bayesian models and latent class methods in the population health research. In collaborative research, she has been serving as lead statistician and co-Investigator on multiple NIH, CDC and foundation grants, with the applications to environmental health sciences, psychiatry and mental health, substance abuse, and child health. She holds a PhD in Biostatistics and a certificate in survey sampling from the University of Michigan.
PhD, 2009, University of Michigan
MS, 2004, Bowling Green State University
BA, 2002, Nankai University
Member, American Statistical Association
Member, International Biometrics Society, ENAR
Member, International Chinese Statistical Association
Member, American Public Health Association
Honors & Awards
NIEHS Center Career Development Award, Columbia University, 2016
Calderone Research Prize for Junior Faculty, Columbia University Mailman School of Public Health, 2010
The Department of Biostatistics Teaching Award, Columbia University Mailman School of Public Health, 2010
Edward C. Bryant Scholarship, American Statistical Association, 2009
Otto Hutzinger Award, 27th International Symposium on Halogenated Persistent Organic Pollutants, Tokyo, Japan, 2007
Areas of Expertise
Bayesian Methods, Missing Data, Multilevel Modeling, Survey Sampling, Community-Based Healthcare, Environmental Epidemiology, Mental Health, Addiction/Drug Abuse Treatment
Chen, Q., Elliott, M. R., Haziza, D., Yang, Y., Ghosh, M., Little, R. J. A., Sedransk, J., and Thompson, M. (2017). “Approaches to improving survey-weighted estimates,” Statistical Science, 32(2): 227-248.
Chen, Q., Paik, M. C., Kim, M., andWang, C. (2016). "Using link-preserving imputation for logistic partially linear models with missing covariates", Computational Statistics and Data Analysis, 101, 174-185.
Chen, Q., Gelman, A., Tracy, M., Norris, F., and Galea, S. (2015). "Incorporating the sampling design in weighting adjustments for panel attrition", Statistics in Medicine, 34 (28): 3637-3647.
Chen, Q., Galfalvy, H., and Duan, N. (2013). "Effects of disease misclassification on exposure-disease association," American Journal of Public Health, 103, e67-e73.
Chen, Q. and Wang, S. (2013). "Variable selection for multiply-imputed data with application to dioxin exposure study," Statistics in Medicine, 32, 3646-59.
Chen, Q., Just, A.C., Miller, R.L., Perzanowski, M.S., Goldstein, I.F., Perera, F.P., Whyatt, R.M. (2012). "Using latent class growth analysis to identify childhood wheeze phenotypes in an urban birth cohort," Annals of Allergy, Asthma & Immunology, 108, 311-315.e1.
Chen, Q., Elliott, M.R., and Little, R.J.A. (2012). "Bayesian inference of finite population quantiles from unequal probability samples," Survey Methodology, 38, 203-214.
Chen, Q., Garabrant, D., Hedgeman, E., Little, R.J.A., Elliott, M.R., Gillespie, B., Hong, B., Lee, S., Lepkowski, J., Franzblau, A., Adriaens, P., Demond, A., and Patterson, D. (2010). "Estimation of background serum 2,3,7,8-TCDD concentrations by using quantile regression in the UMDES and NHANES populations," Epidemiology, 21, S51-S57.
Chen, Q., Elliott, M.R., and Little, R.J.A. (2010). "Bayesian penalized spline model-based inference for finite population proportion in unequal probability sampling," Survey Methodology, 36, 23-34.