Nonparametric regression with right-censored covariate via conditional density function.

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Tytuł:: Nonparametric regression with right-censored covariate via conditional density function.
Autorzy:: Jiang H; School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan, China.
Huang L; School of Mathematics, Southwest Jiaotong University, Chengdu, China.
Xia Y; Department of Statistics and Data Science, National University of Singapore, Singapore.; School of Mathematics, University of Electronic Science and Technology of China, Chengdu, China.
Źródło:: Statistics in medicine [Stat Med] 2022 May 20; Vol. 41 (11), pp. 2025-2051. Date of Electronic Publication: 2022 Feb 06.
Typ publikacji:: Journal Article; Research Support, Non-U.S. Gov't
Język:: English
Imprint Name(s):: Original Publication: Chichester ; New York : Wiley, c1982-
MeSH Terms:: Penicillamine*/therapeutic use
Computer Simulation ; Humans ; Survival Analysis
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Contributed Indexing:: Keywords: conditional hazard rate; dependent censoring; estimation bias; kernel smoothing; random censoring
Substance Nomenclature:: GNN1DV99GX (Penicillamine)
Entry Date(s):: Date Created: 20220206 Date Completed: 20220419 Latest Revision: 20220624
Update Code:: 20240105
DOI:: 10.1002/sim.9343
PMID:: 35124839
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Censoring often occurs in data collection. This article, considers nonparametric regression when the covariate is censored under general settings. In contrast to censoring in the response variable in survival analysis, regression with censored covariates is more challenging but less studied in the literature, especially for dependent censoring. We propose to estimate the regression function using conditional hazard rates. The asymptotic normality of our proposed estimator is established. Both theoretical results and simulation studies demonstrate that the proposed method is more efficient than the estimation based on complete observations and other methods, especially when the censoring rate is high. We illustrate the usefulness of the proposed method using a data set from the Framingham heart study and a data set from a randomized placebo-controlled clinical trial of the drug D-penicillamine.
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