Flexible modeling of survival data with covariates subject to detection limits via multiple imputation

DOI10.1016/j.csda.2013.07.027zbMath1471.62028DBLPjournals/csda/BernhardtWZ14OpenAlexW2045198761WikidataQ30690774 ScholiaQ30690774MaRDI QIDQ1615173

Daowen Zhang, Huixia Judy Wang, Paul W. Bernhardt

Publication date: 2 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3816712

zbMATH Keywords

detection limitmultiple imputationaccelerated failure time modelcomplete casecensored predictorseminonparametric distribution

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01)

Related Items (9)

Censored gamma regression with uncertain censoring status ⋮ Spatial prediction in the presence of left-censoring ⋮ Estimation and residual analysis with R for a linear regression model with an interval-censored covariate ⋮ Mixed effects models with censored covariates, with applications in HIV/AIDS studies ⋮ Multiply imputing missing values in data sets with mixed measurement scales using a sequence of generalised linear models ⋮ Special issue on advances in survival analysis ⋮ Quantile regression for survival data with covariates subject to detection limits ⋮ A fast EM algorithm for fitting joint models of a binary response and multiple longitudinal covariates subject to detection limits ⋮ Joint model of accelerated failure time and mechanistic nonlinear model for censored covariates, with application in HIV/AIDS

Uses Software

• survival
• Mcmcpack

Cites Work

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• Linear Mixed Models with Flexible Distributions of Random Effects for Longitudinal Data
• Semi-Nonparametric Maximum Likelihood Estimation
• Estimating the dimension of a model
• The proportional hazards regression with a censored covariate.
• Semiparametric theory and missing data.
• “Smooth” Semiparametric Regression Analysis for Arbitrarily Censored Time-to-Event Data
• Large-sample theory for parametric multiple imputation procedures
• Inference for imputation estimators
• Type I Error Inflation in the Presence of a Ceiling Effect

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