Novel Approaches in Mixture Modeling

Gitta Lubke, Kevin Grimm

Research output: Contribution to journalEditorial

2 Citations (Scopus)

Abstract

This special issue of Structural Equation Modeling: A Multidisciplinary Journal focuses on advances in finite mixture modeling. Finite mixture models are an exciting class of statistical models for data consisting of unmeasured groups. The articles in this special issue focus on novel uses of mixture models, new approaches to examine model selection uncertainty, model fit, model sensitivity, and alternative approaches to search multivariate data for groups.

Original languageEnglish (US)
Pages (from-to)157-158
Number of pages2
JournalStructural Equation Modeling
Volume24
Issue number2
DOIs
StatePublished - Mar 4 2017

Fingerprint

Mixture Modeling
Finite Mixture Models
Finite Mixture
Structural Equation Modeling
Multivariate Data
Model Uncertainty
Mixture Model
Model Selection
Statistical Model
Alternatives
Modeling
Group
uncertainty
Model
Class
Mixture model
Statistical model
Structural equation modeling
Finite mixture
Model uncertainty

Keywords

  • finite mixture
  • latent class analysis
  • mixture model

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Modeling and Simulation
  • Sociology and Political Science
  • Economics, Econometrics and Finance(all)

Cite this

Novel Approaches in Mixture Modeling. / Lubke, Gitta; Grimm, Kevin.

In: Structural Equation Modeling, Vol. 24, No. 2, 04.03.2017, p. 157-158.

Research output: Contribution to journalEditorial

Lubke, Gitta ; Grimm, Kevin. / Novel Approaches in Mixture Modeling. In: Structural Equation Modeling. 2017 ; Vol. 24, No. 2. pp. 157-158.
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