Zhen Chen, Ph.D.

Investigator

Biostatistics & Bioinformatics Branch

NICHD/DIPHR

6710B 3214
20892-7004

301-435-6934

chenzhe@mail.nih.gov

Research Topics

Diagnostic Accuracy and Bayesian Constrained Analysis, with Application in Human Reproductive and Development Studies

My main research interests are in Bayesian methods, diagnostic accuracy, and statistical analysis under constraints, with applications in epidemiological studies in human reproduction and development. In many epidemiological studies, a priori constraints exist on model parameters. In these cases, I develop Bayesian approaches to adequately account for these constraints to obtain more efficient statistical estimates. To estimate diagnostic accuracy parameters when a gold standard does not exist, I propose new sensitivity analysis framework to allow investigators to vary some tuning parameters in a scientifically sensible way. I also devote considerable effort to developing new methods for estimating ROC curves and the associated AUC measures.

Biography

Dr. Chen is a tenure track investigator in the Biostatistics and Bioinformatics Branch at NICHD. He obtained his Ph.D. in statistics in 2001 at University of Connecticut, and was a Research Fellow at NIEHS from 2001 to 2003. He served as an Assistant Professor (Clinical Educator track) in the Department of Biostatistics and Epidemiology at the University of Pennsylvania from 2003 to 2008 and joined NICHD as a Staff Scientist in 2008 before becoming an investigator in 2009.

Selected Publications

  1. Chen Z, Dunson DB. Random effects selection in linear mixed models. Biometrics. 2003;59(4):762-9.

  2. Zhang B, Chen Z, Albert PS. Latent class models for joint analysis of disease prevalence and high-dimensional semicontinuous biomarker data. Biostatistics. 2012;13(1):74-88.

  3. Dunson DB, Chen Z, Harry J. A Bayesian approach for joint modeling of cluster size and subunit-specific outcomes. Biometrics. 2003;59(3):521-30.

  4. Kim S, Chen Z, Zhang Z, Simons-Morton BG, Albert PS. Bayesian Hierarchical Poisson Regression Models: An Application to a Driving Study with Kinematic Events. J Am Stat Assoc. 2013;108(502):494-503.


This page was last updated on July 26th, 2017