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A quantile regression estimator for interval-censored data
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Abstract
We describe an estimating equation that can be used to fit quantile regression models to interval-censored data. The proposed estimator presents important advantages over the existing methods, and can be applied when the data are a mixture of interval-censored, left-censored, and right-censored observations. We describe estimation and inference, report simulation results, and apply the proposed method to analyze the Signal Tandmobiel® data. The necessary R code has been incorporated in the existing R package
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Title: A quantile regression estimator for interval-censored data
Description:
Abstract
We describe an estimating equation that can be used to fit quantile regression models to interval-censored data.
The proposed estimator presents important advantages over the existing methods, and can be applied when the data are a mixture of interval-censored, left-censored, and right-censored observations.
We describe estimation and inference, report simulation results, and apply the proposed method to analyze the Signal Tandmobiel® data.
The necessary R code has been incorporated in the existing R package
c
t
q
r
$\mathtt{c}\mathtt{t}\mathtt{q}\mathtt{r}$
.
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