Bayesian Factor Analysis
Bayesian Factor Analysis is a probabilistic latent-variable method that places prior distributions on the factor loading matrix and the residual variances, then infers a full posterior over these parameters from the observed data. Developed prominently in the Bayesian framework by Lopes and West (2004), it extends classical exploratory and confirmatory factor analysis by quantifying uncertainty in every estimated loading rather than reporting single point estimates.
Source record
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Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
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Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.