Abstract
In survival analysis it is typical to assess the effect of covariates on a duration variable T. Even though the standard methodology assumes that covariates are free from measurement error, this assumption is often violated in practice. The presence of measurement error may alter the usual properties of the standard estimators of regression coeficients. In the present paper we first show, using Monte Carlo methods, that measurement error in covariates induces bias on the usual regression estimators. We then outline an estimation procedure that corrects for the presence of measurement error. Monte Carlo data are then used to assess the performance of the proposed alternative estimators.Keywordsaccelerated failure time modelcensored datacovariatesmeasurement errorreliability ratio
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
