Multidimensional Self-Concept Structure for Preadolescents With Mild Intellectual Disabilities

By Herbert W. Marsh, Daniel K. Tracey, R. Craven. 2006

130 citations recorded by the source corpus.

Subfields: Experimental and Cognitive Psychology, Management Science and Operations Research, Safety Research

View Paper: https://www.semanticscholar.org/paper/c8a23f2dfc8931a539ffd05fbdbe8761cef9ee8b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Experimental and Cognitive Psychology

1. Alexandre J. S. Morin
2. Andrew J. Martin
3. Herbert W. Marsh
4. G. Liem
5. D. McInerney
6. Alexander Seeshing Yeung
7. A. Arens
8. Daniel A. Sass

In Management Science and Operations Research

1. Alexandre J. S. Morin
2. Herbert W. Marsh
3. A. Arens
4. Andrew J. Martin
5. Daniel A. Sass
6. G. Liem
7. Holger Steinmetz
8. D. McInerney

In Safety Research

1. G. Liem
2. Andrew J. Martin
3. Herbert W. Marsh
4. Alexandre J. S. Morin
5. Alexander Seeshing Yeung
6. D. McInerney
7. A. Arens
8. Paul Ginns

Citations in the corpus

• The Big-Fish-Little-Pond Effect and a National Policy of Within-School Ability Streaming (2013, background): “On the other end of the spectrum, Marsh, Tracey, and Craven (2006) showed that preadolescents with intellectual disabilities perceived themselves as less academically competent when they compared themselves with mixed-ability students in regular classes—as a consequence of ‘‘mainstreaming’’—than…”
• Exploratory Structural Equation Modeling (2009, unknown): “However, Marsh, Tracey, and Craven (2005) proposed a hybrid approach based on the juxtaposition of multiple-group tests of measurement invariance and the MIMIC model.”
• Analyzing observed composite differences across groups: Is partial measurement invariance enough? (2013, background): “However, Marsh, Tracey, and Craven (2006) illustrate how to incorporate several grouping variables as well as their interaction in a special form of latent variable model, that is, the multiple indicators multiple causes model (MIMIC model).”
• Testing Measurement Invariance and Comparing Latent Factor Means Within a Confirmatory Factor Analysis Framework (2011, background): “Multiple Indicator Multiple Cause (MIMIC) and hybrid models (Marsh et al., 2006) are also available to compare means, which make fewer assumptions and may provide a richer understanding of one’s data.”
• Holding back and holding behind: Grade retention and students’ non-academic and academic outcomes (2011, methodology): “Kaplan ( 2000 ; see also Joreskog & Sorbom, 1996 ; Marsh et al , 2005 , 2006 ) described the MIMIC approach as akin to multivariate regression modeling in which latent variables (e.”
• A Bifactor Exploratory Structural Equation Modeling Framework for the Identification of Distinct Sources of Construct-Relevant Psychometric Multidimensionality (2016, methodology): “In such situations, a more parsimonious MIMIC approach (Jöreskog & Goldberger, 1975; Marsh et al., 2006; Muthén, 1989) might be more appropriate.”