Principles and practices in small area estimation
Date:
26/04/2013
Organised by:
University of Sheffield
Presenter:
Dr Adam Whitworth, Dept of Geography, University of Sheffield
Level:
Entry (no or almost no prior knowledge)
Contact:
Dr Adam Whitworth, Dept of Geography, University of Sheffield
adam.whitworth@sheffield.ac.uk
Description:
Marking the completion of this one year NCRM funded network into small area estimation methodologies, a one day introductory training event on principles and practices of small area estimation will be held at the University of Sheffield.
Small area estimation of survey data down to small area level has become an increasingly widespread activity as scholars and policy-makers have sought to gain ever more detailed spatial information to better target interventions or resources and to evaluate local policy impacts. Various alternative methodologies have emerged and these fall broadly within either spatial microsimulation or statistical approaches. This one day training event is intended as an introduction to small area estimation for those without experience of the approaches and who wish to learn about the principles, practicalities and key considerations of small area estimation as well as gaining practical hands-on experience of running two common alternative methodological approaches.
The event is free of charge but places are capped due to room capacity and participants are asked to reserve their place in advance by contacting Dr Adam Whitworth, Principal Investigator of the network, at adam.whitworth@sheffield.ac.uk. Lunch and refreshments will be provided on the day. The practical sessions will be conducted in Stata and some familiarity with Stata syntax is desirable although not essential.
Location & date: Information Commons, University of Sheffield, 10:00-4:00
Listen to Adam Whitworth talk about evaluating and improving small area estimation methods in NCRM podcast series /TandE/video/podcasts.php
Cost:
Free
Website and registration:
Region:
Yorkshire and Humberside
Keywords:
Spatial Data Analysis, small area estimation , spatial microsimulation
Related publications and presentations from our eprints archive: