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Ludwig-Maximilians-Universität München (LMU) >
Sonderforschungsbereich 386: Statistische Analyse diskreter Strukturen, Universität München (LMU) >
Discussion papers, SFB 386, LMU München >
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http://hdl.handle.net/10419/31104
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Full metadata record
| DC Field | | Value | | Language |
| dc.contributor.author | | Küchenhoff, Helmut | | en_US |
| dc.contributor.author | | Lederer, Wolfgang | | en_US |
| dc.contributor.author | | Lesaffre, Emmanuel | | en_US |
| dc.date.accessioned | | 2006-04-25 | | en_US |
| dc.date.accessioned | | 2010-05-14T10:10:31Z | | - |
| dc.date.available | | 2010-05-14T10:10:31Z | | - |
| dc.date.issued | | 2006 | | en_US |
| dc.identifier.pi | | urn:nbn:de:bvb:19-epub-1841-6 | | - |
| dc.identifier.uri | | http://hdl.handle.net/10419/31104 | | - |
| dc.description.abstract | | Most epidemiological studies suffer from misclassification in the response and/or the covariates. Since ignoring misclassification induces bias on the parameter estimates, correction for such errors is important. For measurement error, the continuous analog to misclassification, a general approach for bias correction is the SIMEX (simulation extrapolation) originally suggested by Cook and Stefanski (1994). This approach has been recently extended to regression models with a possibly misclassified categorical response and/or the covariates by K¨uchenhoff et al. (2005), and is called the MC-SIMEX approach. To assess the importance of a regressor not only its (corrected) estimate is needed, but also its standard error. For the original SIMEX approach. Carroll et al. (1996) developed a method for estimating the asymptotic variance. Here we derive the asymptotic variance estimators for the MC-SIMEX approach, extending the methodology of Carroll et al. (1996). We also include the case where the misclassification probabilities are estimated by a validation study. An extensive simulation study shows the good performance of our approach. The approach is illustrated using an example in caries research including a logistic regression model, where the response and a binary covariate are possibly misclassified. | | en_US |
| dc.language.iso | | eng | | en_US |
| dc.publisher | | Techn. Univ.; Sonderforschungsbereich 386, Statistische Analyse Diskreter Strukturen München | | en_US |
| dc.relation.ispartofseries | | Discussion paper // Sonderforschungsbereich 386 der Ludwig-Maximilians-Universität München 473 | | en_US |
| dc.subject.ddc | | 310 | | en_US |
| dc.subject.keyword | | misclassification | | en_US |
| dc.subject.keyword | | SIMEX approach | | en_US |
| dc.subject.keyword | | variance estimation | | en_US |
| dc.title | | Asymptotic Variance Estimation for the Misclassification SIMEX | | en_US |
| dc.type | | Working Paper | | en_US |
| dc.identifier.ppn | | 510830471 | | en_US |
| dc.rights | | http://www.econstor.eu/dspace/Nutzungsbedingungen | | - |
| Appears in Collections: | | Discussion papers, SFB 386, LMU München
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