Estimation and residual analysis with R for a linear regression model with an interval‐censored covariate. Issue 5 (8th August 2014)

• Record Type: Journal Article
• Authors: Langohr, Klaus; Melis, Guadalupe Gómez
• Is Part Of: Biometrical journal. Volume 56:Issue 5(2014:Sep.)
• Page Start: 867
• Page End: 885
• Publication Date: 2014-08-08
• Subjects: Biometry -- Periodicals; Medical statistics -- Periodicals; 570.15195
• DOI: 10.1002/bimj.201300204
• Languages: English
• ISSNs: 0323-3847

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>Interval‐censored covariates are sometimes encountered in longitudinal studies and considered as possible predictors in a regression model. This paper, motivated by an AIDS study, proposes an implementation in R for the estimation of parameters and the assessment of the assumptions of a linear regression model with an interval‐censored covariate. The properties of the parameters estimators and the behavior of three proposed residuals are addressed through two simulation studies. Also, guidelines are provided to check the goodness‐of‐fit of the fitted model in terms of the length of the censoring interval of the covariate. The methodology is illustrated with real data coming from the AIDS study. R functions and scripts are provided.</p> </abstract>