Latent variable mixture modeling in psychiatric research--a review and application.

作者: J. Miettunen , T. Nordström , M. Kaakinen , A. O. Ahmed

DOI: 10.1017/S0033291715002305

关键词: Mixture modelLatent class modelLatent variable modelContext (language use)Categorical variablePsychiatryConfirmatory factor analysisLatent variableSorting

摘要: Latent variable mixture modeling represents a flexible approach to investigating population heterogeneity by sorting cases into latent but non-arbitrary subgroups that are more homogeneous. The purpose of this selective review is provide non-technical introduction in cross-sectional context. class analysis used classify individuals homogeneous (latent classes). Factor newer fusion and factor analysis. models adaptable representing categorical dimensional states affairs. This article provides an overview illustrates the application these methods applying them study structure psychotic experiences. flexibility makes complex psychiatric psychological phenomena. They also allow researchers address research questions directly compare viability dimensional, hybrid conceptions constructs.

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