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st: Event History Analysis, 23-25 Nov, Queen's University, Belfast, UK
From
Nick Cox <[email protected]>
To
"'[email protected]'" <[email protected]>
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 [[email protected]].
Please address all questions to him.
Nick
[email protected]
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
[email protected]<mailto:[email protected]>
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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