JOURNAL ARTICLE

Estimation and residual analysis with R for a linear regression model with an interval‐censored covariate

Klaus LangohrGuadalupe Gómez Melis

Year: 2014 Journal:   Biometrical Journal Vol: 56 (5)Pages: 867-885   Publisher: Wiley

Abstract

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.

Keywords:
Covariate Statistics Mathematics Residual Regression analysis Confidence interval Interval estimation Estimation Linear regression Linear model Econometrics Algorithm

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15
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0.76
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Citation History

Topics

Statistical Methods and Inference
Physical Sciences →  Mathematics →  Statistics and Probability
Fuzzy Systems and Optimization
Physical Sciences →  Mathematics →  Statistics and Probability
Statistical Methods and Bayesian Inference
Physical Sciences →  Mathematics →  Statistics and Probability

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