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Latent class (LC) choice models analyze these data in a way that accounts for heterogeneity by allowing different population segments (latent classes) to express different preferences in making their choices.
After performing a latent class analysis, you might wish to investigate the relationship between class membership and external variables. A popular three-step approach is to first estimate the latent class model of interest (step 1), then assign individuals to latent classes using their posterior class membership probabilities (step 2), and subsequently investigate the association between the assigned class memberships and external variables (step 3).
与GUI集群，DFactor，回归，Step3, Markov和Choice模块相比的其他模型蒙特卡罗模拟选项多个imputation选项n倍验证和坚持选项额外的输出和保存选项使用保存的参数(例如，fo
Replication weights may be used to handle designs where respondents
allocate a number of votes (purchases, points) among the various choice alternatives.
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