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
From MaRDI portal
Publication:5879967
DOI10.1080/24754269.2018.1522576OpenAlexW2891487774WikidataQ90405199 ScholiaQ90405199MaRDI QIDQ5879967
Publication date: 7 March 2023
Published in: Statistical Theory and Related Fields (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/24754269.2018.1522576
Related Items (1)
Cites Work
- Unnamed Item
- Approximate conditional likelihood for generalized linear models with general missing data mechanism
- Semiparametric theory and missing data.
- A new instrumental method for dealing with endogenous selection
- Analysis of multivariate missing data with nonignorable nonresponse
- Likelihood Methods and Nonparametric Tests
- Tuning Parameter Selection in the LASSO with Unspecified Propensity
- Likelihood adjusted for nonignorable missing covariate values with unspecified propensity in generalized linear models
- Penalized pairwise pseudo likelihood for variable selection with nonignorable missing data
- Semiparametric Pseudo-Likelihoods in Generalized Linear Models With Nonignorable Missing Data
- On varieties of doubly robust estimators under missingness not at random with a shadow variable
- Optimal pseudolikelihood estimation in the analysis of multivariate missing data with nonignorable nonresponse
This page was built for publication: 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