Keywords
Categorical variableLatent class modelLatent variableLatent variable modelFactor analysisPopulationClass (philosophy)EconometricsComputer scienceStatisticsMachine learningArtificial intelligenceMathematicsMedicine
Affiliated Institutions
Related Publications
Investigating population heterogeneity with factor mixture models.
Sources of population heterogeneity may or may not be observed. If the sources of heterogeneity are observed (e.g., gender), the sample can be split into groups and the data ana...
Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study
Abstract Mixture modeling is a widely applied data analysis technique used to identify unobserved heterogeneity in a population. Despite mixture models' usefulness in practice, ...
Advances in Behavioral Genetics Modeling Using Mplus: Applications of Factor Mixture Modeling to Twin Data
Abstract This article discusses new latent variable techniques developed by the authors. As an illustration, a new factor mixture model is applied to the monozygotic–dizygotic t...
Should substance use disorders be considered as categorical or dimensional?
ABSTRACT Aims This paper discusses the representation of diagnostic criteria using categorical and dimensional statistical models. Conventional modeling using categorical or con...
Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm
Summary. This paper discusses the analysis of an extended finite mixture model where the latent classes corresponding to the mixture components for one set of observed variables...
Publication Info
- Year
- 2006
- Type
- article
- Volume
- 31
- Issue
- 6
- Pages
- 1050-1066
- Citations
- 180
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
180
OpenAlex
Cite This
Bengt Muthén,
Tihomir Asparouhov
(2006).
Item response mixture modeling: Application to tobacco dependence criteria.
Addictive Behaviors
, 31
(6)
, 1050-1066.
https://doi.org/10.1016/j.addbeh.2006.03.026
Identifiers
- DOI
- 10.1016/j.addbeh.2006.03.026