Combining Data from Multiple Administrative and Survey Sources for Statistical Purposes 2017
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.
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.
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
ADRCE-training Zhang 040 - 2017
7th November 2017 – 8th November 2017
Prof Li-Chun Zhang
The course will be held at the Data Science Building, DS05 (Floor 1), Swansea University Medical School, Singleton Park, Swansea, SA2 8PP. Participants will need to make their own accommodation arrangements.
Thanks to ESRC funding we are able to offer this course at reduced rates as follows:
The course fee includes course materials, light lunch and morning and afternoon refreshments. Travel and accommodation are to be arranged and paid for by the participant.
Course places are limited and registration by 31 October 2017 is strongly recommended.