Centre for Statistics

CfS short course on statistical issues in meta-analysis

About this course

There will be 9 lectures in total (Monday, Wednesday, Thursday for 3 weeks) starting on Monday 18th March. 

This short course will review the practice of meta-analysis, with a focus on statistical issues that arise, and recent research on them. These include use of fixed- versus random-effects meta-analysis, difficulties specific to small sample sizes, and network meta-analysis. The course will be taught primarily by Prof Ken Rice, a biostatistics professor at the University of Washington, Seattle, who is an active in meta-analysis research. Course participants should have an understanding of standard regression methods. Further knowledge of statistical methods and theory may be helpful but is not required or expected.

Schedule

Lectures will take place at 10am--11am on the following dates:

Mon 18th March -- JCMB 5323

Wed 20th March -- JCMB 5323

Thurs 21st March -- Bayes 4.45

Mon 25th March -- Bayes 5.46

Wed 27th March -- JCMB 5323

Thu 28th March -- Bayes 5.46

Mon 1st April -- Bayes 5.46

Wed 3rd April -- JCMB 5323

Thurs 4th April -- Bayes 5.46

Registration

Registration for this course is now open.

Short course registration

 

Professor Ken Rice

Ken is a professor in the Department of Biostatistics at the University of Washington, where he has been a faculty member since 2004. Prior to this, he worked as a postdoc in the MRC Biostatistics Unit, under the supervision of David Spiegelhalter, who also advised his PhD work. Going back further, he completed Cambridge's Diploma in Mathematical Statistics, working with Doug Easton. His undergraduate training was in mathematics, at Churchill College, Cambridge. He was elected a Fellow of the American Statistical Association in 2018.

Organised by Torben Sell (torben.sell@ed.ac.uk).

 

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CfS short course on statistical issues in meta-analysis

Professor Ken Rice (University of Washington) will present a short course on meta analysis during his extended visit in Semester 2.

JCMB 5323 or Bayes 5.46 (see schedule)