Latent Class Analysis

By Αγγελική Β. Χωρίκη. 2016

1,479 citations recorded by the source corpus.

Subfields: Complementary and alternative medicine

View Paper: https://www.semanticscholar.org/paper/6750469a23b015065095cb115619d5484b39d746

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In Complementary and alternative medicine

Citations in the corpus

Variable-Centered, Person-Centered, and Person-Specific Approaches (2018, methodology): “…models, cluster analyses) is quickly growing in popularity due to the finer-grained detail that it allows (Collins & Lanza, 2013; McCutcheon, 1987; Vermunt & Magidson, 2004).3 This approach is used to identify the dynamics of emergent subpopulations in a sample based on a set of chosen variables,…”
Help seeking as a self-regulated learning strategy and achievement goals: The case of academically talented adolescents (2018, background): “The respondents in a latent class are considered homogeneous with respect to model parameters that characterize their responses (McCutcheon, 1987; Vermunt & Magidson, 2002).”
Covariates and Mixture Modeling: Results of a Simulation Study Exploring the Impact of Misspecified Effects on Class Enumeration (2016, methodology): “In this study, we consider the most basic of finite mixture models, the classic LCA model: a cross-sectional mixture model with binary indicators (Goodman, 2002; Lazarsfeld & Henry, 1968; McCutcheon, 1987).”
Mixture Models: Latent Profile and Latent Class Analysis (2016, background): “An accessible and short introduction to latent class analysis and its variations is given by Vermunt and Magidson (2004).”
Assessing Measurement Invariance in Multiple-Group Latent Profile Analysis (2018, methodology): “To decide the number of latent profiles underlying a population, several models are estimated (varying the number of extracted profiles) and compared using fit statistics such as the Akaike’s information criterion (AIC; Akaike, 1973, 1987), Bayesian information criteria (BIC; Schwarz, 1978), sample ”
What Are the Different Types of Principals Across the United States? A Latent Class Analysis of Principal Perception of Leadership (2014, background): “Instead, we are interested in the nonparametric nature or frequency of item responses to distinguish between subgroups or types of principals (see McCutcheon, 1987).”
Robustness of Stepwise Latent Class Modeling With Continuous Distal Outcomes (2016, background): “LC analysis assumes that individuals belong to one of the T categories of an underlying categorical latent variable X that affects the responses (Goodman, 1974; Hagenaars, 1990; McCutcheon, 1987).”
Perceived Threat, Social Identification, and Psychological Well‐Being: The Effects of Political Conflict Exposure (2015, methodology): “LCA is thus a statistical technique used to classify individuals within a larger sample into a set of different subpopulations based on individuals’ probability of endorsing each set of items (McCutcheon, 1987; Muthén, 2001).”
Measuring bullying at work with the short-negative acts questionnaire: identification of targets and criterion validity (2019, background): “Among others, McCutcheon (1987) and Hagenaars (1990) suggested to select the model with the lowest BIC.”
Differences in students' metacognitive strategy knowledge, motivation, and strategy use: A typology of self-regulated learners (2016, background): “According to Rost (2006), the average latent class probabilities for the most likely latent class membership as well as the entropy parameters should be higher than .”
Introduction to Latent Class Analysis With Applications (2017, methodology): “LCA can be used to find separate classes of individuals according to the responses provided to the items of a questionnaire (Collins and Lanza ., 2010; Magidson & Vermunt 2000; Lazarsfeld, 1950).”
Latent Class Analysis (2021, background): “The key assumption made for any latent variable model is that the latent variable or variables explain all associations between the indicators, as implied by the assumption of local independence (Vermunt & Magidson, 2004b).”