Semiparametric maximum likelihood for missing covariates in parametric regression

DOI10.1007/S10463-006-0047-7zbMath1107.62023OpenAlexW2106629999MaRDI QIDQ870501

Zhiwei Zhang, Howard E. Rockette

Publication date: 12 March 2007

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10463-006-0047-7

zbMATH Keywords

EfficiencyAsymptotic normalityParametric regressionInfinite-dimensional M-estimationMissing at randomMissing covariatesProfile likelihoodSemiparametric likelihood

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Nonparametric regression and quantile regression (62G08) Linear inference, regression (62J99)

Related Items (3)

Semiparametric Bayesian multiple imputation for regression models with missing mixed continuous-discrete covariates ⋮ Improving estimation efficiency for two-phase, outcome-dependent sampling studies ⋮ Semi-parametric Bayesian analysis of binary responses with a continuous covariate subject to non-random missingness

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