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The University of Southampton
Southampton Statistical Sciences Research Institute

Combining Data from Multiple Administrative and Survey Sources for Statistical Purposes

Course Summary
Day one provides a general introduction to combining multiple administrative and survey datasets for statistical purposes. A total-error framework is presented for integrated statistical data, which provides a systematic overview of the origin and nature of the various potential errors. The most typical data configurations are illustrated and the relevant statistical methods reviewed.

Day two covers a handful of selected statistical methods. Training will be given on the techniques of data fusion, or statistical matching, by which joint statistical data is created from separate marginal observations. The participants will be introduced to several imputation or adjustment techniques, in the presence of constraints arising from overlapping data sources.

Target Audience:
This course is ideal for social and medical researchers with interests in combining data from multiple sources or analysing data from different sources; staff at National Statistical Institutes (or similar organisations) who are involved in the design, management and quality assurance of statistical processes based on data from multiple sources including censuses, administrative data and sample surveys.

Pre-requisites:
Understanding of the following are required: central concepts of statistical uncertainty (such as bias, variance, confidence interval) and distribution, basic knowledge of data cleaning and imputation, basic experience/skill of R for statistical computing. Methodological training, knowledge and experience will be helpful.

Further course details can be found here

Podcast for some of our previous courses can be found here

Course Code ADRCE-training034 Zhang - 2017

Course Dates 8th June 2017 – 9th June 2017

Places Available 26

Course Leader Prof Li-Chun Zhang

Course Description
Course Contents:

  • Life-cycle of integrated statistical data and transformation processes
  • A framework of error sources associated with data integration
  • Population coverage and unit errors
  • Uncertainty and techniques of categorical data fusion, or statistical matching
  • Imputation and adjustment methods subjected to micro- and macro-level constraints

Learning Outcomes:
By the end of the course participants will have gained:

  • Understanding of potential errors and statistical uncertainty involved in data integration
  • Ability to apply relevant concepts and methods in practice
  • Appreciation of opportunities and challenges of inference based on data integration

Supplementary Items

FeesFor UK registered students (£30 per day)
£60.00

FeesFor staff at UK academic institutions, RCUK funded researchers, UK public sector staff and staff at UK registered charity organisations (£60 per day)
£120.00

FeesFor all other participants (£220 per day)
£440.00

FeesFor ACRC-E/ADS Staff (FOC)£0.00

Location
University of Southampton - Building 39Venue Details

University of Southampton,
Southampton Statistical Sciences Research Institute,
Building 39,
Southampton,
SO17 1BJ

Additional Information
The course will be held at the Southampton Statistical Sciences Research Institute, Building 39, University of Southampton, Southampton, SO17 1BJ. Participants will need to make their own accommodation arrangements.

https://www.southampton.ac.uk/about/visit.page

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