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Estimation and residual analysis with R for a linear regression model with an interval‐censored covariate
Author(s) -
Langohr Klaus,
Melis Guadalupe Gómez
Publication year - 2014
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.201300204
Subject(s) - covariate , statistics , mathematics , residual , regression analysis , confidence interval , interval estimation , estimation , linear regression , linear model , econometrics , algorithm , management , economics
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.