Investigating population heterogeneity with factor mixture models.

By Gitta H. Lubke, B. Muthén. Psychological methods, 2005

1,123 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Genetics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/01435c50750a5304f006de4cd41354e20814d126

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Citations in the corpus

The person-oriented approach to burnout: A systematic review (2016, methodology): “Furthermore, the different type and trajectory solutions found can be compared to each other with rigorous tests (e.g., bootstrapped likelihood ratio test) (Lubke & Muthén, 2005).”
Implicit Theories, Epistemic Beliefs, and Science Motivation: A Person-Centered Approach (2012, background): “Consistent with recommended practices among LPA researchers (Lubke & Muthén, 2005; Pastor et al., 2007) solutions with varying numbers of latent classes were tested and theory, past empirical evidence, characteristics of each profile (e.g., size), and interpretability 23 were considered in arriving…”
A Multifoci Person-Centered Perspective on Workplace Affective Commitment: A Latent Profile/Factor Mixture Analysis (2011, methodology): “FMAs represent a cost-efficient way of including correlations between the indicators by allowing them to be simultaneously related to a categorical latent variable (the LPA model) and to a continuous latent variable (as in the common factor model; Lubke & Muthén, 2005).”
Attempted Validation of the Scores of the VARK: Learning Styles Inventory With Multitrait–Multimethod Confirmatory Factor Analysis Models (2010, methodology): “Furthermore, factor mixture models (Bauer & Curran, 2004; Lubke & Muthén, 2005) could be used to evaluate whether the VARK scores come from a mixture of populations with different factor structures of learning styles.”
Discovering Unobserved Heterogeneity in Structural Equation Models to Avert Validity Threats (2013, background): “As a consequence, it is necessary to differentiate between the following two types of heterogeneity: (1) observed heterogeneity when subpopulations are defined a priori based on known variables and (2) unobserved heterogeneity when the subpopulations in the data are unknown (Lubke and Muthén 2005).”
Modeling Unobserved Heterogeneity Using Latent Profile Analysis: A Monte Carlo Simulation (2013, methodology): “This technique has proven effective in improving the rate of admissible solutions in LCAs and LPAs (e.g., Lubke & Muthén, 2005, 2007; Nylund et al., 2007).”
Person-Centered Methodologies in the Organizational Sciences (2018, background): “In addition, mixture models may also be extended to hybrid factor mixture models (Lubke & Muthén, 2005) that can be used to control for underlying global tendencies (Morin et al., 2011; Morin & Marsh, 2015), probe the underlying nature of psychological constructs (Clark et al., 2013; Masyn,…”
UvA-DARE ( Digital Academic Repository ) Simpson ' s paradox in psychological science : a practical guide (2017, neutral): “…similar analytical approaches to tackle the presence and characteristics of subpopulations exist, including factor mixture www.frontiersin.org August 2013 | Volume 4 | Article 513 | 9 models (Lubke and Muthen, 2005), latent profile models (Halpin et al., 2011) and propensity scores (Rubin, 1997).”
Implementing Restricted Maximum Likelihood Estimation in Structural Equation Models (2013, background): “…of variance (MANOVA; Raykov, 2001), item response theory (Takane & Deleeuw, 1987), categorical data analysis (Muthén, 1984), mixture modeling (Lubke & Muthén, 2005), and meta-analysis (Cheung, 2008, 2010, in Correspondence should be addressed to Mike W.-L. Cheung, Department of Psychology,…”
Heteroscedastic factor mixture analysis (2010, methodology): “This latter case has been explored through factor mixture models (Lubke and Muthén, 2005), which are a combination of latent class analysis (Vermunt and Magidson, 2003) and common factor analysis.”
Multiple-Group Analysis of Similarity in Latent Profile Solutions (2016, methodology): “LPA is thus similar to a CFA except that the latent variable is categorical (reflecting profiles that represent groupings of persons) rather than continuous (reflecting latent factors that represent groupings of 232 Organizational Research Methods 19(2) variables) (Lubke & Muthén, 2005).”
Modeling Epistemic and Ontological Cognition: Philosophical Perspectives and Methodological Directions (2008, methodology): “To fully assess the construct and predictive validity of scores from this model, a procedure called factor mixture analysis ( Lubke & Muthen, 2005 ) must be used.”
The construct of psychophysiological reactivity: Statistical and psychometric issues (2013, background): “Of note, person-centered approaches to physiological reactivity can also be combined with longitudinal assessment if the primary interest is identifying unique patterns of change over time within a sample (Collins & Lanza, 2010; Lubke & Muthén, 2005; Nagin, 2005).”