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Guolo, Annamaria (2007) A Flexible Approach to Measurement Error Correction in Case-Control Studies. [Working Paper] WORKING PAPER SERIES, 8/2007 . , PADOVA

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Abstract (english)

We investigate the use of prospective likelihood methods to analyze retrospective case-control data where some of the covariates are measured with error. We show that prospective methods can be applied and the case-control sampling scheme can be ignored if one adequately models the distribution of the error-prone covariates in the case-control sampling scheme. Indeed, subject to this, the prospective likelihood methods result in consistent estimates and information standard errors are asymptotically correct. However, the distribution of such covariates is not the same in the population and under case-control sampling, dictating the need to model the distribution flexibly. In this paper, we illustrate the general principle by modeling the distribution of the error-prone covariates using the skewnormal distribution. The performance of the method is evaluated through simulation studies, which show satisfactory results in terms of bias and coverage. Finally, the method is applied to the analysis of two data sets which refer, respectively, to a cholesterol study and a study on breast cancer.

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EPrint type:Working Paper
Anno di Pubblicazione:June 2007
More information:Pubblicato anche in: Biometrics - Volume 64(4), pp. 1207-1214
Key Words:Likelihood, Logistic regression, Measurement error, Regression calibration, Rectrospective study, Skewnormal distribution.
Settori scientifico-disciplinari MIUR:Area 13 - Scienze economiche e statistiche > SECS-S/01 Statistica
Struttura di riferimento:Dipartimenti > Dipartimento di Scienze Statistiche
Codice ID:8806
Depositato il:25 May 2015 13:16
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