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VERSION:2.0
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20160425T153042Z
DTSTART:20160425T120000Z
DTEND:20160425T130000Z
SUMMARY:Evaluating the quality of survey and administrative data with gen
 eralized multitrait-multimethod models
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}l4-ing5ut9n
 -dfx0zj
DESCRIPTION:Administrative register data are increasingly important in st
 atistics\, but\, like other types of data\, may contain measurement erro
 rs. To prevent such errors from invalidating analyses of scientific inte
 rest\, it is therefore essential to estimate the extent of measurement e
 rrors in administrative data. Currently\, however\, most approaches to e
 valuate such errors  involve either prohibitively expensive audits or co
 mparison with a survey  that is assumed perfect.\n\nWe introduce the "ge
 neralized multitrait-multimethod" (GMTMM) model\, which can be seen as a
  general framework for evaluating the quality of administrative and surv
 ey data simultaneously. This framework allows both survey and register t
 o contain random and systematic measurement errors. Moreover\, it accomm
 odates common features of administrative data such as discreteness\, non
 linearity\, and nonnormality\, improving similar existing models. The us
 e of the GMTMM model is demonstrated by application to linked survey-reg
 ister data from the German Federal Employment Agency on income from and 
 duration of employment\, and a simulation study evaluates the estimates 
 obtained.\n\nThis seminar is presented by Dr Daniel Oberski\, Assistant 
 Professor in the Department of Methodology and Statistics at Tilburg Uni
 versity.
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:Room 2.07\, Humanities Bridgeford Street\, Manchester
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