Submitted by jlongwor on Thu, 10/21/2010 - 9:00am.
Survival Analysis Group Enhancement (SAGE) is a new series of talks aimed at enhancing a general education for people with interests in survival analysis. Since Winter 2011, this has been conducted jointly with the Biostatistics Seminar Series, and is now known as the SAGE/Biostatistics Seminar.
Submitted by jlongwor on Tue, 03/27/2012 - 10:41am.
Apr 20 2012 - 4:00pm
Apr 20 2012 - 4:50pm
Speaker:
Peter Song, Department of Biostatistics, University of Michigan
Location:
MS 431
In this talk, we will present a systematic analysis for the sample size calculation in high-dimensional classification analysis. We illustrate our new methods via a study design that uses proteomics markers to classify post-kidney transplantation patients into stable and rejection classes.
Submitted by jlongwor on Tue, 03/27/2012 - 10:37am.
Apr 13 2012 - 4:00pm
Apr 13 2012 - 4:50pm
Speaker:
Xuewen Lu
Location:
MS 527
We consider variable selection for partially linear single-index models with randomly censored samples. We present simulation results for illustration.
Submitted by jlongwor on Tue, 03/20/2012 - 8:41am.
Mar 30 2012 - 4:00pm
Mar 30 2012 - 4:50pm
Speaker:
Niroshan Withanage
Location:
MS 527
The talk is concerned with diagnostic studies wherein several diagnostic tests, or the same test measured on several occasions, are administered to identify one or more diseases.
Submitted by jlongwor on Tue, 03/20/2012 - 8:41am.
Mar 30 2012 - 4:00pm
Mar 30 2012 - 4:50pm
Speaker:
Niroshan Withanage
Location:
MS 527
The talk is concerned with diagnostic studies wherein several diagnostic tests, or the same test measured on several occasions, are administered to identify one or more diseases.
Submitted by jlongwor on Wed, 03/07/2012 - 10:08am.
Mar 16 2012 - 4:00pm
Mar 16 2012 - 4:50pm
Speaker:
Jason Xu, Alberta Health Services
Location:
MS 527
Statistical models are widely employed to address research questions in biomedical research field. However, there is a lack of definitive evidence on which statistical models perform best in multicenter RCTs with class of complex interventions.
