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ALLSTAT  February 2008

ALLSTAT February 2008

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Subject:

Course on Small Area Estimation (readvertisement)

From:

Virgilio Gomez-Rubio <[log in to unmask]>

Reply-To:

Virgilio Gomez-Rubio <[log in to unmask]>

Date:

Mon, 25 Feb 2008 13:04:22 +0000

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (135 lines)

Dear all,

This a a re-advertisement of a course for which there are still a few
places available. Apologies for any cross-posting.


Best regards,

Virgilio Gomez-Rubio
Research Associate
Department of Epidemiology and Public Health
Imperial College London
-----------

2-DAY SHORT COURSE ON SMALL AREA ESTIMATION

Faculty of Medicine
Imperial College London
St. Mary's Campus, London

9:00 - 17:00, 28-29 February 2008

*) Course instructor

Prof. Partha Lahiri, University of Maryland. 

Dr. Partha Lahiri is Professor of the Joint Program in Survey
Methodology
(JPSM) at the University of Maryland at College Park, and a Research
Professor
of Institute of Social Research, University of Michigan, Ann Arbor.

*) Course outline

The course will describe the main methods and models used in Small Area
Estimation (SAE). SAE applications include the analysis of survey and
administrative data (e.g., estimation of income), analysis of health
data
(e.g., mapping  mortality and morbidity), agriculture (estimation of
crop
production using remote sensing satellite data)  and many others.

SAE methodology will be described in the morning sessions whilst
the afternoon sessions will be devoted to put into practice some of
these
methods using R and WinBUGS.

The methods covered in the course will include design-based estimators,
traditional indirect estimators, mixed-models and Bayesian models. The
practicals will cover how to compute some of these methods using the R
and
WinBUGS software. A working knowledge of R and WinBUGS will be assumed,
i.e.,
there will not be any tutorial on either R or WinBUGS. However, useful
links
will be made available from the course web page for those attendants who
wish
to improve their skills before the course.

The course will take place in the Hynds Computer Lab of the Faculty of
Medicine
and the participants will be able to use these facilities. Note that
this is in
the Faculty of Medicine, Imperial College London at St. Mary's Campus,
and NOT
in the main campus in South Kensington.

The complete address is

Faculty of Medicine
Imperial College London
St. Mary's Campus, Norfolk Place
W2 1PG London - UK

More information on how to arrive can be found at

http://www1.imperial.ac.uk/medicine/contacts/campuses/stmarys/


This course is part of the ESRC National Centre for Research Methods
training
activities and there are reduced fees for ESRC-funded researchers.


*) Summary of course contents

- Day 1, Registration (9:00-9:30)

- Day 1, Morning Session (9:30-12:30)

Introduction to Small Area Estimation, design-based estimation,
synthetic
estimation, composite estimation. Coffee break at 10:45-11:15.

- Day 1, Afternoon Session (14:00-17:00)

Computer session. Coffee break at 15:30-16:00.

- Day 2, Morning Session (9:00-12:30)

Mixed-models (EBLUP, Bayesian models). Coffee break at 10:30-11:00.

- Day 2, Afternoon Session (14:00-17:00)

Computer session. Coffee break at 15:30-16:00.


*) Booking and course fees

Fees for the course are as follows:

£40 for postgraduate students registered at academic institutions

£80 for staff at academic institutions, ESRC-funded researchers and
researchers from charity organisations

£350 for all other participants

This includes the course materials, refreshments and lunch. In order to
book a place for the course, you should contact Virgilio Gomez-Rubio
([log in to unmask]).

*) Funding for postgraduate students

The Quantitative Methods Research Group of the Royal Geographical
Society
(http://www.casa.ucl.ac.uk/QMRG/) has agreed to fund a number of
postgraduates
attending the course. More information in the course web site.

*) More Info

You can find updated information about the course at the following web
site:
   http://www.bias-project.org.uk/SAEcourse

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