Using the EM-algorithm for survival data with incomplete categorical covariates
From MaRDI portal
Publication:1126018
DOI10.1007/BF00128467zbMath0965.62081OpenAlexW2076685900WikidataQ36893462 ScholiaQ36893462MaRDI QIDQ1126018
Joseph G. Ibrahim, Stuart R. Lipsitz
Publication date: 24 July 2001
Published in: Lifetime Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/bf00128467
Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02)
Related Items
Analysis of Survival Data with Missing Measurements of a Time-Dependent Binary Covariate, Maximum likelihood inference for the Cox regression model with applications to missing covariates, Marginal hazards model for multivariate failure time data with auxiliary covariates, Failure time regression with continuous informative auxiliary covariates, Monte Carlo EM for Missing Covariates in Parametric Regression Models, Fitting the log‐F Accelerated Failure Time Model with Incomplete Covariate Data, Bivariate Binary Data Analysis with Nonignorably Missing Outcomes, Marginal regression models with a time to event outcome and discrete multiple source predictors, Maximum Likelihood Analysis of Logistic Regression Models with Incomplete Covariate Data and Auxiliary Information, Maximum Likelihood Methods for Cure Rate Models with Missing Covariates, Frailty Models with Missing Covariates, Subsample ignorable likelihood for accelerated failure time models with missing predictors, Maximum likelihood estimation for linear regression models with right censored outcomes and missing predictors.
Cites Work
