Efficient estimation for the proportional hazards model with bivariate current status data

DOI10.1007/s10985-007-9058-9zbMath1147.62082OpenAlexW2059443055WikidataQ31131221 ScholiaQ31131221MaRDI QIDQ953242

Jianguo Sun, Lianming Wang, Xing-wei Tong

Publication date: 17 November 2008

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

Full work available at URL: http://europepmc.org/articles/pmc4538960

zbMATH Keywords

tablessieve methodefficient estimationcounting processesbivariate current status datacopula model

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02)

Related Items (11)

Regression analysis of informative current status data with the semiparametric linear transformation model ⋮ Semiparametric regression of clustered current status data ⋮ Regression analysis of bivariate current status data under the gamma-frailty proportional hazards model using the EM algorithm ⋮ Copula link-based additive models for bivariate time-to-event outcomes with general censoring scheme ⋮ A semi-parametric weighted likelihood approach for regression analysis of bivariate interval-censored outcomes from case-cohort studies ⋮ Efficient estimation for additive hazards regression with bivariate current status data ⋮ Semiparametric efficient estimation for additive hazards regression with case II interval-censored survival data ⋮ Second-order estimating equations for the analysis of clustered current status data ⋮ Analysis of Multivariate Interval Censoring by Diabetic Retinopathy Study ⋮ A vine copula approach for regression analysis of bivariate current status data with informative censoring ⋮ Semiparametric probit models with univariate and bivariate current-status data

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Cox's regression model for counting processes: A large sample study
• Bayesian copula selection
• Efficient estimation for the proportional hazards model with interval censoring
• The statistical analysis of interval-censored failure time data.
• On assessing the association for bivariate current status data
• Bayesian Models for Multivariate Current Status Data with Informative Censoring
• A Semiparametric Proportional Odds Regression Model for the Analysis of Current Status Data
• Statistical Inference Procedures for Bivariate Archimedean Copulas
• Bivariate current status data with univariate monitoring times
• On the Unique Consistent Solution to the Likelihood Equations
• A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence
• Additive hazards regression with current status data
• Inferences on the Association Parameter in Copula Models for Bivariate Survival Data
• Sieve Estimation for the Proportional-Odds Failure-Time Regression Model With Interval Censoring
• Efficient estimation in additive hazards regression with current status data
• A Proportional Hazards Model for Multivariate Interval‐Censored Failure Time Data
• Age-Specific Incidence and Prevalence: A Statistical Perspective
• Estimation of the Association for Bivariate Interval‐censored Failure Time Data
• Testing Independence for Bivariate Current Status Data

This page was built for publication: Efficient estimation for the proportional hazards model with bivariate current status data