Marginal semiparametric multivariate accelerated failure time model with generalized estimating equations

DOI10.1007/s10985-014-9292-xzbMath1357.62296arXiv1204.0285OpenAlexW2024904863WikidataQ35096948 ScholiaQ35096948MaRDI QIDQ123913

Sangwook Kang, Sy Han Chiou, Junghi Kim, Jun Yan, Sy Han Chiou, Junghi Kim, Sangwook Kang, Jun Yan

Publication date: 19 February 2014

Published in: Lifetime Data Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1204.0285

zbMATH Keywords

efficiencyleast squaresBuckley-James estimatorinduced smoothingmultivariate survival

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Nonparametric statistical resampling methods (62G09) Reliability and life testing (62N05)

Related Items

The semiparametric accelerated trend-renewal process for recurrent event data ⋮ Nonparametric inference in the accelerated failure time model using restricted means ⋮ Bayesian penalized Buckley-James method for high dimensional bivariate censored regression models ⋮ Generalized estimating equations for analyzing multivariate survival data ⋮ Estimation for an accelerated failure time model with intermediate states as auxiliary information ⋮ Efficient parameter estimation for multivariate accelerated failure time model via the quadratic inference functions method ⋮ aftgee ⋮ Comparison of variance estimation methods in semiparametric accelerated failure time models for multivariate failure time data ⋮ An efficient Gehan-type estimation for the accelerated failure time model with clustered and censored data

Uses Software

• geepack

Cites Work

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