Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 0 |
| Since 2007 (last 20 years) | 3 |
Descriptor
| Adolescents | 3 |
| Predictor Variables | 3 |
| Statistical Analysis | 3 |
| Foreign Countries | 2 |
| Adolescent Development | 1 |
| Anxiety | 1 |
| Classification | 1 |
| Dietetics | 1 |
| Females | 1 |
| Gender Differences | 1 |
| Grade 9 | 1 |
| More ▼ | |
Source
| Structural Equation Modeling:… | 3 |
Author
| Hagtvet, Knut A. | 1 |
| Henry, Kimberly L. | 1 |
| Janosz, Michel | 1 |
| Maiano, Christophe | 1 |
| Marsh, Herbert W. | 1 |
| Morin, Alexandre J. S. | 1 |
| Morizot, Julien | 1 |
| Muthen, Bengt | 1 |
| Nagengast, Benjamin | 1 |
| von Soest, Tilmann | 1 |
Publication Type
| Journal Articles | 3 |
| Reports - Research | 3 |
Education Level
| Secondary Education | 2 |
| Elementary Secondary Education | 1 |
| Grade 9 | 1 |
| High Schools | 1 |
Audience
| Researchers | 1 |
Location
| Canada (Montreal) | 1 |
| Norway | 1 |
Laws, Policies, & Programs
Assessments and Surveys
| Beck Anxiety Inventory | 1 |
What Works Clearinghouse Rating
Morin, Alexandre J. S.; Maiano, Christophe; Nagengast, Benjamin; Marsh, Herbert W.; Morizot, Julien; Janosz, Michel – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Substantively, this study investigates potential heterogeneity in the developmental trajectories of anxiety in adolescence. Methodologically, this study demonstrates the usefulness of general growth mixture analysis (GGMA) in addressing these issues and illustrates the impact of untested invariance assumptions on substantive interpretations. This…
Descriptors: Adolescents, Adolescent Development, Anxiety, Statistical Analysis
von Soest, Tilmann; Hagtvet, Knut A. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
This article presents several longitudinal mediation models in the framework of latent growth curve modeling and provides a detailed account of how such models can be constructed. Logical and statistical challenges that might arise when such analyses are conducted are also discussed. Specifically, we discuss how the initial status (intercept) and…
Descriptors: Statistical Analysis, Predictor Variables, Structural Equation Models, Adolescents
Henry, Kimberly L.; Muthen, Bengt – Structural Equation Modeling: A Multidisciplinary Journal, 2010
Latent class analysis (LCA) is a statistical method used to identify subtypes of related cases using a set of categorical or continuous observed variables. Traditional LCA assumes that observations are independent. However, multilevel data structures are common in social and behavioral research and alternative strategies are needed. In this…
Descriptors: Statistical Analysis, Probability, Classification, Grade 9

Peer reviewed
Direct link
