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Tenko Raykov; Christine DiStefano; Natalja Menold – Structural Equation Modeling: A Multidisciplinary Journal, 2024
This article is concerned with the assumption of linear temporal development that is often advanced in structural equation modeling-based longitudinal research. The linearity hypothesis is implemented in particular in the popular intercept-and-slope model as well as in more general models containing it as a component, such as longitudinal…
Descriptors: Structural Equation Models, Hypothesis Testing, Longitudinal Studies, Research Methodology
Clark, D. Angus; Nuttall, Amy K.; Bowles, Ryan P. – International Journal of Behavioral Development, 2021
Hybrid autoregressive-latent growth structural equation models for longitudinal data represent a synthesis of the autoregressive and latent growth modeling frameworks. Although these models are conceptually powerful, in practice they may struggle to separate autoregressive and growth-related processes during estimation. This confounding of change…
Descriptors: Structural Equation Models, Longitudinal Studies, Risk, Accuracy
Ferrando, Pere J. – Psicologica: International Journal of Methodology and Experimental Psychology, 2015
The standard two-wave multiple-indicator model (2WMIM) commonly used to analyze test-retest data provides information at both the group and item level. Furthermore, when applied to binary and graded item responses, it is related to well-known item response theory (IRT) models. In this article the IRT-2WMIM relations are used to obtain additional…
Descriptors: Item Response Theory, Structural Equation Models, Goodness of Fit, Statistical Analysis
Coulombe, Patrick; Selig, James P.; Delaney, Harold D. – International Journal of Behavioral Development, 2016
Researchers often collect longitudinal data to model change over time in a phenomenon of interest. Inevitably, there will be some variation across individuals in specific time intervals between assessments. In this simulation study of growth curve modeling, we investigate how ignoring individual differences in time points when modeling change over…
Descriptors: Individual Differences, Longitudinal Studies, Simulation, Change
Kern, Ben D.; Graber, Kim C. – Measurement in Physical Education and Exercise Science, 2017
Program satisfaction, self-efficacy to change, and willingness to change, are dispositions that influence physical education teacher change. The study purpose was to validate an instrument measuring program satisfaction, self-efficacy to change, and willingness to change relative to teachers' likelihood to change. A 15-item Teacher Change…
Descriptors: Physical Education Teachers, Test Validity, Questionnaires, Self Efficacy
Madjar, Nir; Kushnir, Talma; Bachner, Yaacov G. – Advances in Health Sciences Education, 2015
Perceived psychosocial abilities (i.e., competence in addressing the psychosocial aspects of patient care) and low frustration tolerance (LFT) (i.e., intolerance of physical or emotional discomfort) have been established as significant attributes of experienced medical professionals. We aimed to expand our understanding of the role motivation…
Descriptors: Communication Skills, Medical Students, Student Motivation, Prediction
Symonds, Jennifer; Dietrich, Julia; Chow, Angela; Salmela-Aro, Katariina – Developmental Psychology, 2016
Underpinned by stage-environment fit and job demands-resources theories, this study examined how adolescents' anxiety, depressive symptoms, and positive functioning developed as they transferred from comprehensive school to further education, employment or training, or became NEET (not in education, employment, or training), at age 16 years, in…
Descriptors: Foreign Countries, Adolescents, Mental Health, Education Work Relationship
Grimm, Kevin J. – Structural Equation Modeling: A Multidisciplinary Journal, 2012
Latent difference score (LDS) models combine benefits derived from autoregressive and latent growth curve models allowing for time-dependent influences and systematic change. The specification and descriptions of LDS models include an initial level of ability or trait plus an accumulation of changes. A limitation of this specification is that the…
Descriptors: Structural Equation Models, Time, Change, Coding
Whittaker, Tiffany A. – Journal of Experimental Education, 2012
Model modification is oftentimes conducted after discovering a badly fitting structural equation model. During the modification process, the modification index (MI) and the standardized expected parameter change (SEPC) are 2 statistics that may be used to aid in the selection of parameters to add to a model to improve the fit. The purpose of this…
Descriptors: Structural Equation Models, Goodness of Fit, Sample Size, Statistical Analysis
Grimm, Kevin; Zhang, Zhiyong; Hamagami, Fumiaki; Mazzocco, Michele – Multivariate Behavioral Research, 2013
We propose the use of the latent change and latent acceleration frameworks for modeling nonlinear growth in structural equation models. Moving to these frameworks allows for the direct identification of "rates of change" and "acceleration" in latent growth curves--information available indirectly through traditional growth…
Descriptors: Structural Equation Models, Change, Individual Differences, Mathematics Skills
Mayer, Axel; Steyer, Rolf; Mueller, Horst – Structural Equation Modeling: A Multidisciplinary Journal, 2012
We present a 3-step approach to defining latent growth components. In the first step, a measurement model with at least 2 indicators for each time point is formulated to identify measurement error variances and obtain latent variables that are purged from measurement error. In the second step, we use contrast matrices to define the latent growth…
Descriptors: Statistical Analysis, Measurement, Structural Equation Models, Error of Measurement
Ferrando, Pere Joan; Anguiano-Carrasco, Cristina – Structural Equation Modeling: A Multidisciplinary Journal, 2011
This article proposes a comprehensive approach based on structural equation modeling for assessing the amount of trait-level change derived from faking-motivating situations. The model is intended for a mixed 2-wave 2-group design, and assesses change at both the group and the individual level. Theoretically the model adopts an integrative…
Descriptors: Structural Equation Models, Change, Personality Measures, Deception
Choi, Jaehwa; Harring, Jeffrey R.; Hancock, Gregory R. – Multivariate Behavioral Research, 2009
Throughout much of the social and behavioral sciences, latent growth modeling (latent curve analysis) has become an important tool for understanding individuals' longitudinal change. Although nonlinear variations of latent growth models appear in the methodological and applied literature, a notable exclusion is the treatment of growth following…
Descriptors: Causal Models, Structural Equation Models, Longitudinal Studies, Change
Yuan, Ke-Hai; Kouros, Chrystyna D.; Kelley, Ken – Structural Equation Modeling: A Multidisciplinary Journal, 2008
When a covariance structure model is misspecified, parameter estimates will be affected. It is important to know which estimates are systematically affected and which are not. The approach of analyzing the path is both intuitive and informative for such a purpose. Different from path analysis, analyzing the path uses path tracing and elementary…
Descriptors: Computation, Structural Equation Models, Statistical Bias, Factor Structure
Grimm, Kevin J.; Ram, Nilam – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Nonlinear growth curves or growth curves that follow a specified nonlinear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this article we describe how a variety of sigmoid curves can be fit using the M"plus" structural modeling program and the nonlinear…
Descriptors: Structural Equation Models, Statistical Analysis, Computer Software, Longitudinal Studies
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