Regression Analysis with Covariates Missing at Random: A Piece-wise Nonparametric Model for Missing Covariates

DOI10.1080/03610920802618392zbMath1318.62140OpenAlexW2012731203MaRDI QIDQ3652788

Yang Zhao

Publication date: 16 December 2009

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920802618392

zbMATH Keywords

semiparametric modelmaximum likelihoodmissing covariatespiece-wise nonparametric model

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Point estimation (62F10) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (3)

Maximum likelihood estimation of missing data probability for nonmonotone missing at random data ⋮ 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

• Unnamed Item
• On maximum likelihood estimation in parametric regression with missing covariates
• Inference and missing data
• Semiparametric Methods for Response-Selective and Missing Data Problems in Regression
• A Pseudoscore Estimator for Regression Problems With Two-Phase Sampling
• On Profile Likelihood
• Nonparametric and Semiparametric Models for Missing Covariates in Parametric Regression

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