Xin M. Tu, PhD

Associate Chair
Professor of Biostatistics
Professor of Psychiatry
Director, Statistical Consulting Service
Director, Division of Psychiatric Statistics
Ph.D. (1989) Duke University


 

Contact Information:

University of Rochester
Dept of Biostatistics and Computational Biology
601 Elmwood Avenue Box 630
Rochester, New York 14642
 
Office: Saunders Research Building 4239
Phone: (585) 275-0413
Fax: (585) 273-1031
E-mail: Xin_Tu@urmc.rochester.edu
Xin M. Tu, PhD

Curriculum Vitae


Data and Programming for Applied Categorical and Count Data Analysis

Software Website

 

Research Interests

Xin Tu (Ph.D.) is Professor of Biostatistics and Psychiatry in the Department of Biostatistics and Computational Biology and Department of Psychiatry. He is the Director of the Statistical Consulting Center and the Director of the Psychiatric Statistics Division within the Department of Biostatistics and Computational Biology.

Dr. Tu has done important work in the areas of U-statistics, longitudinal data analysis, survival analysis with interval censoring and truncation, and pooled testing, and has successfully applied his novel development to addressing important methodological problems in HIV/AIDS, mental health and psychosocial research. In recent years, he and his group have been focusing on issues arising in research on accuracy of proxy outcomes, causal treatment effects from group-based and multi-layered psychosocial interventions, and interpersonal interactions and their effects on individual behavior and health outcomes in the social network context. They have been successfully addressing all these issues using the functional response models (FRM). For example, their most recent work on causal inference using rank-based methods such as the Mann-Whitney-Wilcoxon rank sum test using the FRM has been published as a feature article in the April Issue of Statistics in Medicine (Wu, Han, Chen and Tu, X.M. Statistics in Medicine, 33(8): 1261-1271, 2014). 

Dr. Tu has co-edited two books, Modern Clinical Trial Analysis (2012, Springer Science) and Social Networking: Recent Trends, Emerging Issues and Future Outlook (2013, Nova Science), and co-authored two books, Modern Applied U-Statistics (2007, Wiley) and Applied Categorical and Count Data Analysis (2012, CRC),10 book chapters, and over 170 peer-reviewed publications. His methodological research covers a broad range, including his earlier work on censored- and truncated-data analysis, pooled testing, power analysis, and instrumentation, and his more recent work on causal inference, mediation models and social network data analysis. He has mentored 5 PhD, 3 postdoctoral and numerous Master’s-level students in biostatistics. The PhD and postdoctoral students all have successfully secured faculty and research positions at major research universities and firms, including the Johns Hopkins and Cornell Universities. Dr. Tu has been consulting and collaborating with a large number of trans-disciplinary investigators to provide support for their statistical designs, methods and reporting questions needs. His consulting and collaborative roles in numerous studies have made significant contributions to a number of fields of research and practice.


Selected Publications

  • He, H., Wang, W., Crits-Christoph, P., Gallop, R., Tang, W., Chen, D.G. and Tu, X.M.  On the implication of structural zeros as independent variables in regression analysis: Applications to alcohol research.  Journal of Data Science, in press. 
  • Wu, P., Han, Y., Chen, T., and Tu, X.M. (2014). Causal inference for Mann-Whitney-Wilcoxon rank sum and other nonparametric statistics. Statistics in Medicine, 33(8): 1261-1271.  This publication is a featured article in this issue of the Journal. 
  • Gunzler, D., Tang, W., Lu, N., Wu, P. and Tu, X.M.  A class of distribution-free models for longitudinal mediation analysis.  Psychometrika, in press.
  • Wu, P., Tu, X.M., and Kowalski, J. (2014).  On assessing model fit for distribution-free longitudinal models under missing data.  Statistics in Medicine, 33:143-157. 
  • Feng, C., Wang, H., Han, Y., Xia, Y., and Tu, X. M. (2013).  The Mean value theorem and Taylor's expansion in statistics.  The American Statistician, 67:245-248.
  • Yu, Q., Chen, R., Tang, W., He, H., Gallop, R., Crits-Christoph, P., Hu, J. and Tu, X.M. (2013). Distribution-free models for longitudinal count responses with over-dispersion and structural zeros.  Statistics in Medicine, 32: 2390-2405. 
  • Ma, Y., Tang, W., Yu, Q. and Tu, X.M. (2010).  Modeling concordance correlation coefficient for longitudinal study data.  Psychometrika, 75, 99-119.    
  • Silenzio, V., Duberstein, P., Tang, W., Lu, N., Tu, X.M., and Homan, C. (2009).  Connecting the invisible dots: reaching lesbian, gay, and bisexual adolescents and young adults through online social networks.  Social Science and Medicine, 69(3): 469-474. 
  • Ma, Y., Tang, W., Feng, C. and Tu, X.M. (2008).  Inference for Kappas for longitudinal study data: Applications to sexual health research.  Biometrics, 64: 781-789. 
  • Lamberti, J.S., Olson, D., Crilly, J.F., Olivares, T., Williams, G.C., Tu, X.M., Tang, W., Wiener, K., Dvorin, S., Dietz, M.B., Bushey, M.P. and Maharaj, K. (2006).  Prevalence of the metabolic syndrome among patients receiving Clozapine.  The American Journal of Psychiatry, 163: 1273-1276.   
  • Tu, X.M., Kowalski, J., Zhang, J., Lynch, K. and Crits-Christoph, P. (2004).  Power analyses for longitudinal trials and other clustered study design.  Statistics in Medicine, 23: 2799-2815.   
  • Mendoza-Blanco, J.R., Tu, X.M., and Iyengar, S. (1996).  Bayesian inference on prevalence using a missing-data approach with simulation-based techniques: application to HIV screening.  Statistics in Medicine, 15:2161-2176.  
  • Tu, X.M., Litvak, E., and Pagano, M. (1995).  On the informativeness and accuracy of pooled testing in estimating prevalence of a rare disease: application to HIV screening.  Biometrika, 82:287-297. 
  • DeGruttola, V. and Tu, X.M. (1994).  Modeling progression of CD4-lymphocyte count and its relationship to survival time.  Biometrics, 50:1003-1014.  
  • Litvak, E., Tu, X.M., and Pagano, M. (1994).  Screening for the presence of a disease by pooling sera samples.  Journal of the American Statistical Association, 89:424-434.   
  • Tu, X.M., Meng, X. and Pagano, M. (1993). The AIDS epidemic: estimating survival after AIDS diagnosis from surveillance data.  Journal of the American Statistical Association, 88:26-36.   

Books