Nonparametric regression using local kernel estimating equations for correlated failure time data

DOI10.1093/biomet/asm081zbMath1437.62667OpenAlexW1986418083MaRDI QIDQ3631484

Xihong Lin, Zhangsheng Yu

Publication date: 10 June 2009

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://biostats.bepress.com/harvardbiostat/paper53

zbMATH Keywords

asymptoticsmarginal modelsandwich estimatorclustered survival dataweighted kernel smoothingworking-independence kernel estimator

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Reliability and life testing (62N05)

Related Items (9)

Local linear regression on correlated survival data ⋮ Time-varying coefficients in a multivariate frailty model: application to breast cancer recurrences of several types and death ⋮ Semiparametric Frailty Models for Clustered Failure Time Data ⋮ Weighted Estimator for the Linear Transformation Models with Multivariate Failure Time Data ⋮ Kernel regression for cause-specific hazard models with nonparametric covariate functions ⋮ Goodness‐of‐fit tests in proportional hazards models with random effects ⋮ Nonparametric Estimation for Censored Mixture Data With Application to the Cooperative Huntington’s Observational Research Trial ⋮ Bayesian local influence of generalized failure time models with latent variables and multivariate censored data ⋮ Gaining efficiency via weighted estimators for multivariate failure time data

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