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
More information regarding our courses can be found here.
Podcast for some of our previous courses can be found here.
16th October 2017 – 17th October 2017
Dr Jorg Drechsler
The fee per day is: