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Latent GOLD®'s cluster module provides the state-of-the-art in cluster analysis based on latent class models. Latent classes are unobservable (latent) subgroups or segments. Cases within the same latent class are homogeneous on certain criteria (variables), while cases in different latent classes are dissimilar from each other in certain important ways.
"This program by Jay Magidson and Jeroen Vermunt is simply splendid! With great graphics, and intuitive commands, it includes new, state-of-the-art technical features like Bayes constants to help avoid boudary solutions, methods to diagnose and relax local dependence, and automatic testing of multiple start values. The features are too many to list..." John Uebersax.
Responses from conjoint/discrete choice data consists of a single choice from each choice task (Choice sets).
Two important applications of Scale Adjusted Latent Class (SALC) models are:
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