A pairwise likelihood augmented Cox estimator for left-truncated data

DOI10.1111/biom.12746zbMath1415.62142OpenAlexW2750654660WikidataQ38602542 ScholiaQ38602542MaRDI QIDQ3119809

Sehee Kim, Jing Qin, Yi Li, Fan Wu, Rajiv Saran

Publication date: 13 March 2019

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc6402872

zbMATH Keywords

empirical processcomposite likelihoodself-consistency\(U\)-processchronic kidney diseaseCox estimator

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) Order statistics; empirical distribution functions (62G30) Reliability and life testing (62N05)

Related Items (5)

Inference on semi-parametric transformation model with a pairwise likelihood based on left-truncated and interval-censored data ⋮ A pairwise pseudo‐likelihood approach for left‐truncated and interval‐censored data under the Cox model ⋮ Combined estimating equation approaches for the additive hazards model with left-truncated and interval-censored data ⋮ Model selection and model averaging for analysis of truncated and censored data with measurement error ⋮ Semiparametric methods for left-truncated and right-censored survival data with covariate measurement error

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