Likelihood adjusted for nonignorable missing covariate values with unspecified propensity in generalized linear models
From MaRDI portal
Publication:4558438
DOI10.5705/ss.202015.0437zbMath1406.62080OpenAlexW2588385756MaRDI QIDQ4558438
Fang Fang, Jun Shao, Jiwei Zhao
Publication date: 22 November 2018
Published in: Statistica Sinica (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.5705/ss.202015.0437
identifiabilitygeneralized linear modelspseudo-likelihoodinstrumentsadjusted likelihoodnonignorable missing covariate data
Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)
Related Items (15)
Statistical methods without estimating the missingness mechanism: a discussion of ‘statistical inference for nonignorable missing data problems: a selective review’ by Niansheng Tang and Yuanyuan Ju ⋮ Stability enhanced variable selection for a semiparametric model with flexible missingness mechanism and its application to the ChAMP study ⋮ Weighted rank estimation for nonparametric transformation models with nonignorable missing data ⋮ Tuning Parameter Selection in the LASSO with Unspecified Propensity ⋮ Empirical likelihood approach for change-point estimation based on residuals in piecewise linear models ⋮ Approximate conditional likelihood for generalized linear models with general missing data mechanism ⋮ Estimation for nonignorable missing response or covariate using semi-parametric quantile regression imputation and a parametric response probability model ⋮ Regularized quantile regression for ultrahigh-dimensional data with nonignorable missing responses ⋮ Likelihood identifiability and parameter estimation with nonignorable missing data ⋮ Semiparametric inference for estimating equations with nonignorably missing covariates ⋮ Generalized signed-rank estimation for regression models with non-ignorable missing responses ⋮ Semiparametric likelihood for estimating equations with non-ignorable non-response by non-response instrument ⋮ Nonparametric regression with selectively missing covariates ⋮ On classification with nonignorable missing data ⋮ On the maximal deviation of kernel regression estimators with NMAR response variables
This page was built for publication: Likelihood adjusted for nonignorable missing covariate values with unspecified propensity in generalized linear models