PhD, Biostatistics 2010 * University of Michigan * Dissertation: Flexible Methods for Clustered Event History data * Advisors: Drs. Jack Kalbfleisch and Douglas Schaubel
MA, Statistics 2005 * University of Missouri-Columbia * Thesis: Regression Analysis of Longitudinal Data with Informative Observation and Censoring Times * Advisor: Dr. Tony(Jianguo) Sun
BS, Applied Mathematics 2002 * Fudan University, China
Work Experience
Assistant Professor 2011 - present Department of Biostatistics, Vanderbilt University
Postdoctoral Research Fellow 2010 - 2011 Fred Hutchinson Cancer Research Center
Selected Publications
Gifford KA, Liu D, Carmona H, Lu Z, Romano R, Tripodis Y, Martin B, Kowall N, and Jefferson AL (2014) Inclusion of an Informant Yields Strong Associations Between Cognitive Complaint and Longitudinal Cognitive Outcomes in Non-demented Elders. Journal of Alzheimer's Disease, In press
Liu D, Zheng Y, Prentice RL and Hsu L (2014) Projecting Population Risk with Time-to-Event Data. Journal of the American Statistical Association, 109: 514-524
Gifford KA, Liu D, Lu Z, Tripodis Y, Cantwell N, Palmisano J, Kowall N, and Jefferson AL (2014) The Source of Cognitive Complaints Differentially Predicts Diagnostic Conversion Among Non-demented Older Adults. Alzheimers & Dementia, 10: 319-327
Liu, D, Kalbfleisch, JD and Schaubel, DE (2014) Methods for Estimating Center Effects on Recurrent Events. Statistics in Bioscience, 6: 19-37
Liu, D, Cai, T and Zheng, Y (2012) Evaluating the Predictive Value of Biomarkers with Stratified Case-Cohort Design. Biometrics, 68: 1219-1227
Liu, D, Schaubel, DE and Kalbfleisch, JD (2012) Computationally Efficient Marginal Models for Clustered Recurrent Event Data. Biometrics, 68: 637-647
Liu, D, Kalbfleisch, JD and Schaubel, DE (2011) A Positive Stable Frailty Model for Clustered Failure Time Data with Covariate Dependent Frailty. Biometrics, 67: 8-17
Sun, J , Sun, L and Liu, D (2007) Regression Analysis of Longitudinal Data in the Presence of Informative Censoring and Observation Times. Journal of the American Statistical Association, 102: 1397-1406. code