Generating Synthetic Data for Statistical Disclosure Control
This short course will provide a detailed overview of the topic, covering all important aspects relevant for the synthetic data approach. Starting with a short introduction to data confidentiality in general and synthetic data in particular, the workshop will discuss the different approaches to generating synthetic datasets in detail. Possible modelling strategies and analytical validity evaluations will be assessed and potential measures to quantify the remaining risk of disclosure will be presented.
The aim is to provide the participants with hands on experience, the course will include practical sessions using R, in which the students generate and evaluate synthetic data based on real data examples.
The course intends to summarize the state of the art in synthetic data. The main focus will be on practical implementation and not so much on the motivation of the underlying statistical theory. Participants may be academic researchers or practitioners from statistical agencies working in the area of data confidentiality and data access. Basic knowledge in R is expected. Some background in Bayesian statistics is helpful but not obligatory.
Further information can be found here
2nd May 2017 – 3rd May 2017
Dr Jörg Drechsler
The fee per day is:
Our courses are very popular and are often oversubscribed. If you cannot attend a course you have registered for, it is essential to kindly notify us a minimum of 30 days in advance so that your place can be released for another attendee. Details of our cancellation policy are here. Please see our full course list here.
All fees include event materials, lunch, morning and afternoon tea. They do not include travel and accommodation costs.
Course places are limited and registration by 25th April is strongly recommended.