Multiple imputation methods for recurrent event data with missing event category

DOI10.1002/CJS.5550340408zbMath1115.62116OpenAlexW1968761139MaRDI QIDQ5295959

Douglas E. Schaubel, Jianwen Cai

Publication date: 31 July 2007

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/cjs.5550340408

zbMATH Keywords

semiparametric modelmissing datamultivariate failure time dataproportional rates modelEuro-DOPPSEuropean component of Dialysis Outcomes and Practice Patterns Studyimproper imputation

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02)

Related Items (7)

A semiparametric additive rates model for multivariate recurrent events with missing event categories ⋮ An additive-multiplicative rates model for multivariate recurrent events with event categories missing at random ⋮ A semiparametric additive rates model for the weighted composite endpoint of recurrent and terminal events ⋮ Semiparametric temporal process regression of survival-out-of-hospital ⋮ Estimating treatment effects on the marginal recurrent event mean in the presence of a terminating event ⋮ Semiparametric additive marginal regression models for multiple type recurrent events ⋮ Analysis of cyclic recurrent event data with multiple event types

Cites Work

• Unnamed Item
• Unnamed Item
• Longitudinal data analysis using generalized linear models
• Cox's regression model for counting processes: A large sample study
• Towards a general asymptotic theory for Cox model with staggered entry
• Multiple imputation for the Cox proportional hazards model with missing covariates
• Marginal means/rates models for multiple type recurrent event data
• Weak convergence and empirical processes. With applications to statistics
• Multiple Imputation Methods for Estimating Regression Coefficients in the Competing Risks Model with Missing Cause of Failure
• Survival Analysis Using Auxiliary Variables Via Multiple Imputation, with Application to AIDS Clinical Trial Data
• Multiple Imputation After 18+ Years
• Some Graphical Displays and Marginal Regression Analyses for Recurrent Failure Times and Time Dependent Covariates
• Rate/Mean Regression for Multiple-Sequence Recurrent Event Data with Missing Event Category
• Asymptotic Statistics
• The Generalized Estimating Equation Approach When Data Are Not Missing Completely at Random
• Semiparametric Regression for the Mean and Rate Functions of Recurrent Events
• Multiple imputation methods for testing treatment differences in survival distributions with missing cause of failure
• Proper and Improper Multiple Imputation
• Some Simple Robust Methods for the Analysis of Recurrent Events
• Inference for imputation estimators
• Statistical models based on counting processes

This page was built for publication: Multiple imputation methods for recurrent event data with missing event category