General Information:

This group meets every 2-3 weeks to discuss and work on statistical problems of mutual interest arising in biomedical applications, host seminars, and study current methodological developments in the literature. Meetings are informal, and all interested faculty and students are encouraged to participate.

See below for this semester's schedule and for abstracts and slides for talks from previous semesters.

Location:

This semester, we will meet at 1108 SAS Hall on the NCSU campus (Building 32A on the campus map) unless otherwise specified. Parking is available at the Visitor Pay Lots on North campus (visitor parking). Alternatively, visitors may proceed to the Visitor's Center on Stinson Drive. Tell the attendant you are attending a seminar in the Statistics Department in SAS Hall. If you have problems, call Sasha Miao at 515-1902.

Please contact Daowen Zhang for more information on the group, the next meeting, to be put on the mailing list, or anything else.

Spring 2013 meetings:

All seminars are 4:00 - 5:00 pm in 1108 SAS Hall unless otherwise indicated

• Upcoming -- Seminars

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Previous semester activities:

• Fall 2012 -- Seminars
• Spring 2012 -- Seminars
• Fall 2011 -- Seminars
• Spring 2011 -- Seminars
• Fall 2010 -- Seminars
• Spring 2010 -- Seminars
• Fall 2009 -- Seminars
• Spring 2009 -- Seminars
• Fall 2008 -- Seminars
• Spring 2008 -- On hiatus due to heavy interviewing; no meetings
• Fall 2007 -- Seminars
• Spring 2007 -- Seminars
• Fall 2006 -- Seminars
• Spring 2006 -- Seminars
• Fall 2005 -- Seminars
• Spring 2005 -- Seminars
• Fall 2004 -- Seminars
• Spring 2004 -- Seminars
• Fall 2003 -- Seminars
• Spring 2003 -- On hiatus due to heavy interviewing; no meetings
• Fall 2002 -- Seminars
• Spring 2002 -- Seminars
• Fall 2001 -- Seminars
• Spring 2001 -- Seminars
• Fall 2000 -- On hiatus, no meetings
• Spring 2000 -- Causal inference, continued
• Fall 1999 -- Causal inference
• Spring 1999 -- Joint modeling of longitudinal and primary endpoint data
• Fall 1998 -- Models and methods for inference with missing data

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