Disentangling Shape from Level Effects in Person-Centered Analyses: An Illustration Based on University Teachers’ Multidimensional Profiles of Effectiveness

By Alexandre J. S. Morin, Herbert W. Marsh. 2015

283 citations recorded by the source corpus.

Subfields: Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/1e5b22e38c4a7fa47612c84ee60ade27026146b5

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In Computer Networks and Communications

Citations in the corpus

Person-Centered Methodologies in the Organizational Sciences (2018, background): “…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, Henderson, & Greenbaum, 2010), or even…”
Career adaptability profiles and their relationship to adaptivity and adapting (2015, background): “While it can be argued that shape differences are essential if person-centered approaches are to provide substantive additional utility beyond person-centered analyses, the extent towhich level or shape differences aremeaningful strongly depends on their theoretical bases (Morin & Marsh, 2015).”
Further Reflections on Disentangling Shape and Level Effects in Person-Centered Analyses: An Illustration Exploring the Dimensionality of Psychological Health (2016, methodology): “Discussion Shape and Level Effects: The importance of Preliminary Measurement Models Morin and Marsh (2015) noted that a key implicit assumption of person-centered analyses is that extracted profiles should be qualitatively (shape) different from one another and that a latent profile solution where…”
Motivation profiles at work: A self-determination theory approach (2016, methodology): “This is likely to produce better tailored and cost efficient interventions for particular subpopulations of employees (Morin & Marsh, 2015).”
A person‐centered approach to commitment research: Theory, research, and methodology (2016, background): “For example, in a study of university teachers, Morin and Marsh (2015) sought to estimate profiles of specific strengths and weaknesses on a wide array of teaching competencies while also taking into account teachers’ global level of effectiveness.”
Mixture Modeling for Lifespan Developmental Research (2019, methodology): “…2010), to test the measurement invariance of psychometric measures across unobserved subpopulations (Tay, Newman, & Vermunt, 2011), or simply to control for a general tendency shared among indicators in order to estimate latent profiles controlled for this shared tendency (Morin & Marsh, 2015).”
Fuzzy Profiles (2018, methodology): “…in interpretation, we calculated “elbow plots” of the BIC and C-AIC values of each profile solution to illustrate the gains in model fit with each additional profile specified; scholars should select the profile solution at the point with which the slope of the plot flattens (Morin & Marsh, 2015).”
Multiple-Group Analysis of Similarity in Latent Profile Solutions (2016, methodology): “An alternative, which is becoming more frequent in recent applications of mixture models, is to rely on factor scores saved from preliminary measurement models (e.g., Kam et al., 2016; Morin & Marsh, 2015).”
Latent profile analysis: A review and “how to” guide of its application within vocational behavior research (2020, background): “Possible solutions are the estimation of factor mixture models with continuous factors to account for globality, or the estimation of latent categorical variables from residual covariances (Morin, Boudrias, Marsh, Madore, & Desrumaux, 2016; Morin & Marsh, 2015).”