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st: Event History Analysis, 23-25 Nov, Queen's University, Belfast, UK


From   Nick Cox <n.j.cox@durham.ac.uk>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
Subject   st: Event History Analysis, 23-25 Nov, Queen's University, Belfast, UK
Date   Mon, 18 Oct 2010 17:10:41 +0100

This is forwarded on behalf of John McDonald [John.Mcdonald@IOE.AC.UK]. 

Please address all questions to him. 

Nick 
n.j.cox@durham.ac.uk 

Event History Analysis
Lecturers: John 'Mac' McDonald and Alfonso Miranda, Institute of Education
23 - 25 November 2010, Queen's University, Belfast

This 3-day course introduces students to the main alternative methods used
to analyse event history data. The course will provide students with an
understanding of the aims of some methods of event history analysis; how to
apply them and how to interpret the results. It acts as a practical introduction
to modelling the time to a single event, modelling competing risks for multiple
types of events, multilevel models for modelling times to recurrent events and
models including unobserved heterogeneity. The course provides a hands on
workshops on the use of Stata for event history analysis. Datasets used in the
workshops are from two British birth cohorts studies, BCS70 and NCDS.

Further information can be obtained from:
http://www.ncrm.ac.uk/
http://www.ioe.ac.uk/research/16369.html
admincentre.courses@ioe.ac.uk<mailto:admincentre.courses@ioe.ac.uk>

Fees:
1.  £90    -  UK registered postgraduate student
2.  £180    -  Staff at UK academic institution
3.  £180    -  ESRC funded researcher
4.  £180    -  Registered charity organisation
5.  £660  -  Other
All fees include event materials, lunch, morning and afternoon tea.

John `Mac' McDonald
Director of ADMIN Training and Capacity Building Programme and
Professor of Longitudinal Social Statistics, Institute of Education, London

ADMIN (Administrative Data - Methods, Inference and Network) is a research node of
the ESRC National Centre for Research Methods. We teach short courses on methods
for the linkage of survey and administrative data and methods for the analysis of linked
data and administrative data, e.g. the National Pupil Database.


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