An EM algorithm for regression analysis with incomplete covariate information

DOI10.1080/10629360600565202zbMath1108.62034OpenAlexW2046423508MaRDI QIDQ3432739

Howard E. Rockette, Zhiwei Zhang

Publication date: 18 April 2007

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10629360600565202

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Point estimation (62F10)

Related Items (6)

Semiparametric maximum likelihood for missing covariates in parametric regression ⋮ Empirical and conditional likelihoods for two‐phase studies ⋮ Two-phase outcome-dependent studies for failure times and testing for effects of expensive covariates ⋮ A gradient-based algorithm for semiparametric models with missing covariates ⋮ Semi-parametric Bayesian analysis of binary responses with a continuous covariate subject to non-random missingness ⋮ Semiparametric model for regression analysis with nonmonotone missing data

Cites Work

• On maximum likelihood estimation in parametric regression with missing covariates
• Inference and missing data
• A conditional model for incomplete covariates in parametric regression models
• Monte Carlo EM for Missing Covariates in Parametric Regression Models

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