Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/31008 
Kompletter Metadatensatz
DublinCore-FeldWertSprache
dc.contributor.authorSchneeweiss, Hansen
dc.contributor.authorAugustin, Thomasen
dc.date.accessioned2005-10-18-
dc.date.accessioned2010-05-14T10:09:23Z-
dc.date.available2010-05-14T10:09:23Z-
dc.date.issued2005-
dc.identifier.pidoi:10.5282/ubm/epub.1821en
dc.identifier.piurn:nbn:de:bvb:19-epub-1821-5en
dc.identifier.urihttp://hdl.handle.net/10419/31008-
dc.description.abstractA measurement error model is a regression model with (substantial) measurement errors in the variables. Disregarding these measurement errors in estimating the regression parameters results in asymptotically biased estimators. Several methods have been proposed to eliminate, or at least to reduce, this bias, and the relative efficiency and robustness of these methods have been compared. The paper gives an account of these endeavors. In another context, when data are of a categorical nature, classification errors play a similar role as measurement errors in continuous data. The paper also reviews some recent advances in this field.en
dc.language.isoengen
dc.publisher|aLudwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen |cMünchenen
dc.relation.ispartofseries|aDiscussion Paper |x452en
dc.subject.jelC13en
dc.subject.jelC20en
dc.subject.jelC24en
dc.subject.jelC25en
dc.subject.ddc519en
dc.subject.keywordMeasurement errorsen
dc.subject.keyworderror in variablesen
dc.subject.keywordmisclassificationen
dc.subject.keywordefficiency comparisonen
dc.subject.keywordsurvival analysisen
dc.subject.stwRegressionen
dc.subject.stwSchätztheorieen
dc.subject.stwTheorieen
dc.titleSome recent advances in measurement error models and methods-
dc.type|aWorking Paperen
dc.identifier.ppn501294406en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen

Datei(en):
Datei
Größe
188.86 kB





Publikationen in EconStor sind urheberrechtlich geschützt.