Full information maximum likelihood estimation in factor analysis with a large number of missing values

DOI10.1080/00949655.2014.995656OpenAlexW2079814531MaRDI QIDQ5222314

Miyuki Imada, Sunyong Kim, Yutaka Kano, Manabu Yoshida, Masato Matsuo, Kei Hirose

Publication date: 1 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1312.5458

zbMATH Keywords

EM algorithmfactor analysisfull information maximum likelihood

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to social sciences (62P25)

Related Items

Sparse multivariate regression with missing values and its application to the prediction of material properties, Robust clustering via mixtures of \(t\) factor analyzers with incomplete data

Cites Work

• Analysis of NMAR missing data without specifying missing-data mechanisms in a linear latent variate model
• Identifying variables responsible for data not missing at random
• Estimation for structural equation models with missing data
• Estimation for the multiple factor model when data are missing
• EM algorithms for ML factor analysis
• Conjugate Gradient Acceleration of the EM Algorithm
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item