Analysis of NMAR missing data without specifying missing-data mechanisms in a linear latent variate model

DOI10.1016/j.jmva.2011.04.007zbMath1217.62075OpenAlexW1994579134MaRDI QIDQ549917

Keiji Takai, Yutaka Kano

Publication date: 19 July 2011

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2011.04.007

zbMATH Keywords

conditional independenceasymptotic robustnesscomplete-case analysismulti-sample analysis in SEMselection and pattern-mixture modelsshared-parameter model

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Factor analysis and principal components; correspondence analysis (62H25) Estimation in multivariate analysis (62H12)

Related Items

Consistency, bias and efficiency of the normal-distribution-based MLE: the role of auxiliary variables ⋮ Unnamed Item ⋮ Missing data mechanisms and homogeneity of means and variances-covariances ⋮ Full information maximum likelihood estimation in factor analysis with a large number of missing values

Uses Software

• Mplus
• LISREL
• EQS

Cites Work

• Bayesian analysis of nonlinear structural equation models with mixed continuous, ordered and unordered categorical, and nonignorable missing data
• Normal distribution based pseudo ML for missing data: with applications to mean and covariance structure analysis
• Handbook of latent variable and related models.
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• Asymptotics of estimating equations under natural conditions.
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• Identifiability of full, marginal, and conditional factor analysis models
• Measurement invariance, factor analysis and factorial invariance
• On the relationship between the higher-order factor model and the hierarchical factor model
• Bayesian analysis of nonlinear structural equation models with nonignorable missing data
• Notes on factorial invariance
• Parametric Models for Response-Biased Sampling
• Missing responses in generalised linear mixed models when the missing data mechanism is nonignorable
• Analysis of multivariate missing data with nonignorable nonresponse
• A Latent Variable Model with Non-Ignorable Missing Data
• Simple Computation of Maximum Likelihood Estimates in Latent Class Model with Equality and Constant Constraints
• Robustness of normal theory statistics in structural equation models*
• Inference and missing data
• Missing Covariates in Generalized Linear Models When the Missing Data Mechanism is Non-ignorable
• A class of pattern-mixture models for normal incomplete data
• Parameter Estimation from Incomplete Data in Binomial Regression When the Missing Data Mechanism is Nonignorable
• Pattern-Mixture Models for Multivariate Incomplete Data with Covariates
• Regression Analysis Under Non-standard Situations: A Pairwise Pseudolikelihood Approach
• Pattern-Mixture Models for Multivariate Incomplete Data
• ASYMPTOTIC ROBUSTNESS IN MULTIPLE GROUP LINEAR-LATENT VARIABLE MODELS
• Informative Drop-Out in Longitudinal Data Analysis
• Local Model Uncertainty and Incomplete-Data Bias (With Discussion)
• Robustness of normal theory methods in the analysis of linear latent variate models
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