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SUMMARY:Measures of Utility for Synthetic Data - Gillian Raab (University 
 of Edinburgh)
DTSTART:20161103T153000Z
DTEND:20161103T163000Z
UID:TALK68971@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:When synthetic data are produced to overcome potential disclos
 ure they   can be used either in place of the original data or\, more comm
 only\, to   allow researchers to develop code that will ultimately be run 
 on the   original data.&nbsp\; The utility of synthetic data can be measur
 ed by   comparing the results of the final analysis with the synthetic and
    original data. This is not possible until the final analysis is   compl
 ete.&nbsp\; General utility measures that measure the overall   difference
 s between the original and synthetic data are more useful for   those crea
 ting synthetic data. This presentation will discuss two such   >measures. 
 The first is a propensity score measure originally proposed   by Woo et. a
 l.\, 2009 and the second is one based on comparing tables\,   suggested by
  Voas and Williamson\, 2001. Their null distributions\, when   the synthes
 is model is "correct" will be discussed as well as their   practical imple
 mentation as part of the synthpop package.
LOCATION:Seminar Room 2\, Newton Institute
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