Semiparametric Box–Cox power transformation models for censored survival observations

DOI10.1093/biomet/92.3.619zbMath1152.62377OpenAlexW2082883684MaRDI QIDQ3597963

Publication date: 29 January 2009

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://biostats.bepress.com/harvardbiostat/paper6

zbMATH Keywords

prediction resampling method accelerated failure time model Mayo biliary cirrhosis data simultaneous confidence interva

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01) Estimation in survival analysis and censored data (62N02)

Related Items (22)

DISTRIBUTION-FREE ESTIMATION OF THE BOX–COX REGRESSION MODEL WITH CENSORING ⋮ A rank-based approach to estimating monotone individualized two treatment regimes ⋮ Evaluating marker-guided treatment selection strategies ⋮ Monotone rank estimation of transformation models with length-biased and right-censored data ⋮ Discussion of “A Risk-Based Measure of Time-Varying Prognostic Discrimination for Survival Models,” by C. Jason Liang and Patrick J. Heagerty ⋮ Sparse Laplacian shrinkage for nonparametric transformation survival model ⋮ Survival Analysis via Ordinary Differential Equations ⋮ Maximum profile binomial likelihood estimation for the semiparametric Box-Cox power transformation model ⋮ A class of proportional win‐fractions regression models for composite outcomes ⋮ Rank estimation for mean residual life transformation model ⋮ Incorporating short‐term outcome information to predict long‐term survival with discrete markers ⋮ Landmark Prediction of Long-Term Survival Incorporating Short-Term Event Time Information ⋮ Semiparametric Models of Time-Dependent Predictive Values of Prognostic Biomarkers ⋮ Information Ratio Test for Model Misspecification in Quasi-Likelihood Inference ⋮ Profiling heteroscedasticity in linear regression models ⋮ Subgroup specific incremental value of new markers for risk prediction ⋮ The Box-Cox transformation: review and extensions ⋮ Power-transformed linear regression on quantile residual life for censored competing risks data ⋮ Subgroup Specific Incremental Value of New Markers for Risk Prediction ⋮ Estimation for the Power-transformed Varying-coefficient Quantile Regression Model ⋮ Generalized accelerated failure time model with censored data from case-cohort studies ⋮ Landmark estimation of survival and treatment effects in observational studies

This page was built for publication: Semiparametric Box–Cox power transformation models for censored survival observations