Bayesian factor analysis for multilevel binary observations

By Asim Ansari, Kamel Jedidi. 2000

108 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/001740bf3bd548753c9e58317e69adcc10fb3e9a

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Citations in the corpus

High-dimensional maximum marginal likelihood item factor analysis by adaptive quadrature (2005, methodology): “Ansari and Jedidi, 2000; Fox and Glass, 2001) could be employed, but this raises a host of issues, such as appropriate specification of priors to avoid non-recurrent chains and monitoring convergence of MCMC in high-dimensional space.”
Latent Variable Modelling: A Survey * (2007, methodology): “Multilevel factor models for dichotomous and ordinal measures, or equivalently, multilevel item–response models, have been used by, for instance Ansari & Jedidi (2000), Rabe-Hesketh et al. (2004), Goldstein & Browne (2005) and Steele & Goldstein (2006).”
A Bayesian Approach for Estimating Multilevel Latent Contextual Models (2016, unknown): “…Gelman & Hill, 2007; Hamaker & Klugkist, 2011; Zhang, Hamagami, Wang, Nesselroade, & Grimm, 2009), SEM (e.g., Arminger & Muthén, 1998; Kaplan & Depaoli, 2012; Lee, 2007; B. O. Muthén & Asparouhov, 2012; Song & Lee, 2009), and multilevel SEM (e.g., Ansari & Jedidi, 2000; Depaoli & Clifton, 2015).”
A Bayesian Approach to Multilevel Structural Equation Modeling With Continuous and Dichotomous Outcomes (2015, background): “…is uniquely beneficial in the context of categorical data because it can be used to estimate categorical variable models that cannot be analyzed with currently available frequentist approaches (see, e.g., Ansari & Jedidi, 2000; Dunson, 2000; Muthén & Asparouhov, 2012b; Steele & Goldstein, 2006).”
Generalized multilevel structural equation modeling (2004, methodology): “For binary data, MCMC methods have been proposed by Ansari and Jedidi (2000) and Fox and Glas (2001).”
Bayesian Structural Equation Modeling (2007, methodology): “For factor models, which are a special case of SEMs, there is a long history of Bayesian methods (see, for example, Martin and McDonald, 1975; Lee, 1981; Ansari and Jedidi, 2000; Lopes and West, 2004).”
Factor analysis with (mixed) observed and latent variables in the exponential family (2001, methodology): “However, other methods for approximating integrals through simulation are also currently available, in particular in the area of Bayesian computation (Markov Chain Monte Carlo Methods; see Ansari & Jedidi, 2000, for an application to factor analysis for binary data).”