Latent class analysis (LCA) has evolved from a categorical data tool to a broader mixture modeling framework. This volume, part of the CILVR series, highlights LCA’s growth, inspired by C. Mitchell “Chan” Dayton’s contributions, and explores its future in defining subpopulations and integrating measured and latent variables.
Read MoreLatent class analysis (LCA) has evolved from a categorical data tool to a broader mixture modeling framework. This volume, part of the CILVR series, highlights LCA’s growth, inspired by C. Mitchell “Chan” Dayton’s contributions, and explores its future in defining subpopulations and integrating measured and latent variables.
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