John Charlton
Office for National Statistics
1 Drummond Gate
London SW1V2QQ
UK
Imputation-based methods for dealing with incomplete or inconsistent data are used in virtually all National Statistics Institutes (NSIs), and in academic and business research. Currently, these methods are typically based on simple statistical ideas (e.g. nearest neighbours). Also, little is known about the comparative performance of each method, across the wide variety of data sources being used.
Recent, advances in computing capabilities have made possible the application of the more complex statistical modeling techniques. The EUREDIT project will combine recent developments in statistical and computer science to develop and evaluate novel edit and imputation methodologies, focusing on the use of new statistical, neural network and related methods for edit and imputation in large-scale statistical data sets.
In EUREDIT the fundamental approach adopted involves identifying sound scientific and technical, user-oriented criteria to enable a meaningful comparison of current and new promising methods for data editing and imputation.
Invited presentations