Latent factor regression models for grouped outcomes

DOI10.1111/biom.12037zbMath1429.62631OpenAlexW2162248164WikidataQ34224158 ScholiaQ34224158MaRDI QIDQ2861975

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Publication date: 13 November 2013

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4171058

zbMATH Keywords

factor analysisregressionepidemiologymultiple outcomes

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02)

Related Items (2)

Random Effects Misspecification Can Have Severe Consequences for Random Effects Inference in Linear Mixed Models ⋮ Bayesian Models for Multiple Outcomes in Domains With Application to the Seychelles Child Development Study

Uses Software

• BayesDA

Cites Work

• Markov chain Monte Carlo: can we trust the third significant figure?
• Latent Variable Models with Fixed Effects
• Crossed Random Effect Models for Multiple Outcomes in a Study of Teratogenesis
• A Scaled Linear Mixed Model for Multiple Outcomes
• Beyond SEM: General Latent Variable Modeling
• Scaled marginal models for multiple continuous outcomes
• Structural Equation Models
• Bayesian Models for Multiple Outcomes Nested in Domains

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