Multivariate Methods • Latent Class Analysis
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Latent Class Analysis
Group Observations of Categorical Variables
Latent class analysis enables you to find clusters of observations for categorical response variables. A latent variable is an unobservable grouping variable. Each level of the latent variable is called a latent class. The Latent Class Analysis platform fits a latent class model and determines the most likely cluster or latent class for each observation. In most situations, a subject matter expert uses the results of a latent class analysis to create definitions for each latent class based on the characteristics of the class.
Figure 13.1 Example of Latent Class Analysis
Contents 
Overview of the Latent Class Analysis Platform
Example of Latent Class Analysis
Launch the Latent Class Analysis Platform
The Latent Class Analysis Report
Latent Class Model for <k> Clusters Report
Latent Class Analysis Platform Options
Latent Class Analysis Options
Latent Class Model Options
Additional Example of the Latent Class Analysis Platform
Plot Probabilities of Cluster Membership
Statistical Details for the Latent Class Analysis Platform
Latent Class Model Fit
Maximum Number of Clusters

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Help created on 10/11/2018