Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/31122 
Year of Publication: 
2003
Series/Report no.: 
Discussion Paper No. 345
Publisher: 
Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen, München
Abstract: 
For instance nutritional data are often subject to severe measurement error, and an adequate adjustment of the estimators is indispensable to avoid deceptive conclusions. This paper discusses and extends the method of regression calibration to correct for measurement error in Cox regression. Special attention is paid to the modelling of quadratic predictors, the role of heteroscedastic measurement error, and the efficient use of replicated measurements of the surrogates. The method is used to analyze data from the German part of the MONICA cohort study on cardiovascular diseases. The results corroborate the importance of taking into account measurement error carefully.
Subjects: 
Error-in-variables
replication data
heteroscedastic measurement error in quadratic variables
Cox model
regression calibration
MONICA/KORA study
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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