Bayesian semiparametric models for nonignorable missing mechanisms in generalized linear models

DOI10.1080/02664763.2013.794329OpenAlexW2077146358MaRDI QIDQ5129069

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Publication date: 26 October 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2013.794329

zbMATH Keywords

empirical Bayesgeneralized additive modelspline regressionmissing not at randommissing covariate

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items

Bayesian methods for dealing with missing data problems

Uses Software

• WinBUGS
• SemiPar

Cites Work

• Unnamed Item
• Bayesian analysis of zero-inflated regression models
• Nonignorable Missingness in Matched Case-Control Data Analyses
• Robust methods for generalized linear models with nonignorable missing covariates
• Missing Covariates in Generalized Linear Models When the Missing Data Mechanism is Non-ignorable
• Regression Analysis with Missing Covariate Data Using Estimating Equations
• Semiparametric Regression
• Inference Using Conditional Logistic Regression with Missing Covariates
• Bayesian Analysis of Binary and Polychotomous Response Data
• Semiparametric Models for Missing Covariate and Response Data in Regression Models
• Bayesian Analysis for Generalized Linear Models with Nonignorably Missing Covariates
• Missing-Data Methods for Generalized Linear Models
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)

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