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 (R) data. The necessary R code has been incorporated in the existing R package ctqr.
A quantile regression estimator for interval-censored data
Frumento, Paolo
Primo
2022-01-01
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 (R) data. The necessary R code has been incorporated in the existing R package ctqr.File in questo prodotto:
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