Pseudo-partial likelihood for proportional hazards models with biased-sampling data

DOI10.1093/biomet/asp026zbMath1170.62072OpenAlexW1974939280WikidataQ34197544 ScholiaQ34197544MaRDI QIDQ3399074

Wei-Yann Tsai

Publication date: 29 September 2009

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3304552

zbMATH Keywords

EM algorithmright censoringleft-truncationlength-biased datamissing covariateleukemia data

Mathematics Subject Classification ID

Related Items (37)

Composite partial likelihood estimation for length-biased and right-censored data with competing risks ⋮ Semiparametric maximum likelihood estimation for the Cox model with length-biased survival data ⋮ A proportional hazards model for time-to-event data with epidemiological bias ⋮ Combined estimating equation approaches for semiparametric transformation models with length-biased survival data ⋮ Nonparametric and semiparametric regression estimation for length-biased survival data ⋮ Regression analysis for the proportional hazards model with parameter constraints under case-cohort design ⋮ Reweighting estimators for the transformation models with length-biased sampling data and missing covariates ⋮ Censored quantile regression model with time‐varying covariates under length‐biased sampling ⋮ Maximum likelihood and pseudo score approaches for parametric time-to-event analysis with informative entry times ⋮ Estimation for the Cox model with biased sampling data via risk set sampling ⋮ Case-cohort and inference for the proportional hazards model with covariate adjustment ⋮ Statistical inference for case-cohort design under the additive hazards model with covariate adjustment ⋮ Analyzing the general biased data by additive risk model ⋮ Pseudo-likelihood for case–cohort studies under length-biased sampling ⋮ Nonparametric and semiparametric estimators of restricted mean survival time under length-biased sampling ⋮ Regression analysis for outcome-dependent sampling design under the covariate-adjusted additive hazards model ⋮ Assumptions regarding right censoring in the presence of left truncation ⋮ Partially linear transformation model for length-biased and right-censored data ⋮ Composite Partial Likelihood Estimation Under Length-Biased Sampling, With Application to a Prevalent Cohort Study of Dementia ⋮ Rank-based estimation for semiparametric accelerated failure time model under length-biased sampling ⋮ Quantile regression for right-censored and length-biased data ⋮ Semiparametric model of mean residual life with biased sampling data ⋮ Semiparametric quantile-difference estimation for length-biased and right-censored data ⋮ Model diagnostics for the proportional hazards model with length-biased data ⋮ Regression analysis for the additive hazards model with general biased survival data ⋮ An embedded estimating equation for the additive risk model with biased-sampling data ⋮ Missing information principle: a unified approach for general truncated and censored survival data problems ⋮ Proportional hazards model with varying coefficients for length-biased data ⋮ Estimation in a competing risks proportional hazards model under length-biased sampling with censoring ⋮ Composite Estimating Equation Method for the Accelerated Failure Time Model with Length-biased Sampling Data ⋮ Category-Adaptive Variable Screening for Ultra-High Dimensional Heterogeneous Categorical Data ⋮ On semiparametric transformation model with LTRC data: pseudo likelihood approach ⋮ The estimation for the general additive-multiplicative hazard model using the length-biased survival data ⋮ Semiparametric Quantile Regression Analysis of Right‐censored and Length‐biased Failure Time Data with Partially Linear Varying Effects ⋮ Regression Analysis of Length‐biased and Right‐censored Failure Time Data with Missing Covariates ⋮ Variable selection for frailty transformation models with application to diabetic complications ⋮ Composite estimating equation approach for additive risk model with length-biased and right-censored data

This page was built for publication: Pseudo-partial likelihood for proportional hazards models with biased-sampling data