title: Latent variable mixture modeling in psychiatric research--a review and application.
abstract: 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 to provide a non-technical introduction to mixture modeling in a cross-sectional context. Latent class analysis is used to classify individuals into homogeneous subgroups (latent classes). Factor mixture modeling represents a newer approach that represents a fusion of latent class analysis and factor analysis. Factor mixture models are adaptable to representing categorical and dimensional states of affairs. This article provides an overview of latent variable mixture models and illustrates the application of these methods by applying them to the study of the latent structure of psychotic experiences. The flexibility of latent variable mixture models makes them adaptable to the study of heterogeneity in complex psychiatric and psychological phenomena. They also allow researchers to address research questions that directly compare the viability of dimensional, categorical and hybrid conceptions of constructs.
authors.affiliation: Center for Life Course Epidemiology and Systems Medicine,University of Oulu,Oulu,Finland.
authors.forename: J
authors.initials: J
authors.lastname: Miettunen
authors.affiliation: Center for Life Course Epidemiology and Systems Medicine,University of Oulu,Oulu,Finland.
authors.forename: T
authors.initials: T
authors.lastname: Nordström
authors.affiliation: Center for Life Course Epidemiology and Systems Medicine,University of Oulu,Oulu,Finland.
authors.forename: M
authors.initials: M
authors.lastname: Kaakinen
authors.affiliation: Department of Psychiatry,Weill Cornell Medical College - Westchester Division,White Plains, NY,USA.
authors.forename: A O
authors.initials: AO
authors.lastname: Ahmed
mesh_terms: D003430:Cross-Sectional Studies; D005163:Factor Analysis, Statistical; D006801:Humans; D008960:Models, Psychological; D015233:Models, Statistical; D011618:Psychotic Disorders / Q000175:diagnosis*
keywords: Factor mixture models; latent class analysis; psychosis; statistics