Latent Class Models

By Jeroen K. Vermunt. 2004

1,083 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/f38606d7cecab2d0e2e4c23867e691e2e6bd2702

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Citations in the corpus

The influence of social relationships on pro-environment behaviors (2012, methodology): “The basic idea of a latent cluster model is that the probability of a 14 specific response pattern is the average probability of the response pattern given each class or profile, weighted by the prior probability of profile membership (Magidson and Vermunt [23]).”
Group Faultlines (2012, background): “We suggest that future studies with large groups use methodologies such as local dependence in latent class cluster analysis to control for such interdependencies (Clogg, 1995; Patel, Thatcher, & Bezrukova, in press).”
Comparing Typological Structures Across Cultures By Multigroup Latent Class Analysis (2003, background): “In particular, latent class analysis and its extension to multigroup latent class analysis has become more popular in applied social sciences (e.g., Clogg, 1995; Clogg & Goodman, 1985; Hagenaars, 1990, 1993; Langeheine & Rost, 1988; Lazarsfeld & Henry, 1968; McCutcheon, 1987; Rost & Langeheine,…”
The Impact of Ignoring a Level of Nesting Structure in Multilevel Growth Mixture Models: A Monte Carlo Study (2010, methodology): “Traditionally, Latent Class Analysis (LCA), also referred as Latent Class Models (LCM) (Clogg, 1995), is used when the observed indicators are categorical and cross-sectional.”
Patterns of psychological adaptation to divorce after a long-term marriage (2015, methodology): “After having assessed the number of profiles, standard procedures assign each individual to the most probable profile to estimate between-class differences on covariates (Clogg, 1995; Morselli & Passini, 2012).”
On the Analysis of Fraction Subtraction Data: The DINA Model, Classification, Latent Class Sizes, and the Q-Matrix (2011, methodology): “The RDINA model can be viewed as the first part of a restricted latent class model (see Clogg, 1995; Dayton, 1998).”
Addressing cold-start problem in recommendation systems (2008, background): “…ﬁltering, including hard-clustering users into classes [3], simultaneously hard-clustering users and items [16], soft-clustering users and items [8, 11], singular value decomposition [13], inferring item-item similarities [14], probabilistic modeling [3, 11, 12, 20], machine learning [2], and…”
Impact of Misspecifications of the Latent Variance–Covariance and Residual Matrices on the Class Enumeration Accuracy of Growth Mixture Models (2016, background): “…potentially result in the overextraction of spurious latent classes and biased parameter estimates in other types of mixture models (Bauer & Curran, 2004; Heggeseth & Jewell, 2013; Lubke & Muthén, 2007; Lubke & Neale, 2006, 2008; Magidson & Vermunt, 2004; McLachlan & Peel, 2000; Peugh & Fan, 2013).”