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SUMMARY:Statistical Modelling using Linked Data - Issues and Opportunities
  - Ray Chambers (University of Wollongong)
DTSTART:20160708T103000Z
DTEND:20160708T113000Z
UID:TALK66686@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Probabilistic linkage of multiple data sets is now popular and
  widespread. Unfortunately\, there appears to be little corresponding enth
 usiasm for adjusting standard methods of statistical analysis when they ar
 e used with these linked data sets\, even though there is plenty of eviden
 ce from simulation studies that both incorrect links as well as informativ
 e missed links can lead to biased inference. In this presentation I will d
 escribe the key issues that need to be addressed when analysing such linke
 d data and some of the methods that can help. In this context\, I will foc
 us in particular on the simple linear regression model as a vehicle for de
 monstrating how knowledge about the statistical properties of the linkage 
 process as well as summary information about the population distribution o
 f the analysis variables can be used to correct for (or at least alleviate
 ) these inferential problems. Recent research at the Australian Bureau of 
 Statistics on a potential weighting/imputation approach to implementing th
 ese solutions will also be presented.      <br>
LOCATION:Seminar Room 1\, Newton Institute
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