Hierarchical Bayes is a modeling method based on statistics that uses probability to predict events. Hierarchical models are multi-level and describe both the behavior of specific respondents (within-unit analysis), as well as the distribution of responses amongst respondents (across-unit analysis). This is in contrast to latent-class models, which typically produce models at the segment level.
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