Xianghua Luo, PhD
Associate Professor, Division of Biostatistics, School of Public Health
Member,
Biostatistics Core, Masonic Cancer Center, University of Minnesota

 

Education: Ph.D., 2005, Biostatistics, Johns Hopkins Bloomberg School of Public Health

Teaches: PubH 8452 Longitudinal Data Analysis, Fall 2014

Peer-Reviewed Publications: via PubMed, Google Scholar

Research Interests: Development and application of methods for recurrent event data, survival data, and longitudinal data; design and analysis of clinical trials. Collaborations include cancer research, blood and marrow transplant (BMT), tobacco use and smoking cessation, and health disparity research.

My methodological research interests include: Recurrent gap time data analysis, Dependent data resampling, Recurrent events under case-crossover design, Survival analysis. Some publications are:

Luo X, Sorock GS. (2008). Analysis of recurrent event data under the case-crossover design with applications to elderly falls. Statistics in Medicine, 27:2890-2901. Some of the R code for simulation studies.

Luo X, Wang M-C, Huang C-Y. (2010). A comparison of various rate functions of a recurrent event process in the presence of a terminal event. Statistical Methods in Medical Research, 19(2):167-182.

Luo X, Huang C-Y*. (2011). Analysis of recurrent gap time data using the weighted risk set method and the modified within-cluster resampling method. Statistics in Medicine, 30(4):301-11. *Both authors contributed equally to the work.

Huang C-Y, Luo X, Follmann D. (2011). A model checking method for the proportional hazards model with recurrent gap time data. Biostatistics, 12(3):535547.

Liao W, Luo X*, Le C, Chu H, Epstein LH, Yu J, Ahluwalis JS, Thomas J. (2013). Analysis of cigarette purchase task instrument data with a left-censored mixed effects model. Experimental and Clinical Psychopharmacology, 21(2):124132. *First author was Luo's thesis advisee. Technical report.

Luo X, Huang C-Y, Wang L. Quantile regression for recurrent gap time data. Biometrics, 2013 Mar 11. doi: 10.1111/biom.12010. [Epub ahead of print]. Technical report. R code for quantile regression.

 

My collaborative research intrestes include but not limited to:

Full CV

Update: September 30, 2014