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Yuan Fang; Lijuan Wang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Dynamic structural equation modeling (DSEM) is a useful technique for analyzing intensive longitudinal data. A challenge of applying DSEM is the missing data problem. The impact of missing data on DSEM, especially on widely applied DSEM such as the two-level vector autoregressive (VAR) cross-lagged models, however, is understudied. To fill the…
Descriptors: Structural Equation Models, Bayesian Statistics, Monte Carlo Methods, Longitudinal Studies
Gniewosz, Burkhard; Gniewosz, Gabriela – International Journal of Behavioral Development, 2018
The present article aims to show how to model longitudinal change in cohort sequential data applying latent true change models using Mplus' multi-group approach. The underlying modeling ideas are described and explained in this article. As an example, change in internalizing problem behaviors between the age of 8 and 13 years is modeled and…
Descriptors: Models, Data, Behavior Problems, Children
Brahm, Taiga; Jenert, Tobias; Wagner, Dietrich – Higher Education: The International Journal of Higher Education Research, 2017
In Switzerland, every student graduating from grammar school can begin to study at a university. This leads to high dropout rates. Although students' motivation is considered a strong predictor of performance, the development of motivation during students' transition from high school to university has rarely been investigated. Additionally, little…
Descriptors: Longitudinal Studies, Business Schools, Foreign Countries, Student Motivation
Retelsdorf, Jan; Becker, Michael; Koller, Olaf; Moller, Jens – British Journal of Educational Psychology, 2012
Background: Assigning students to different school tracks on the basis of their achievement levels is a widely used strategy that aims at giving students the best possible learning opportunity. There is, however, a growing body of literature that questions such positive effects of tracking. Aims: This study compared the developmental trajectories…
Descriptors: Academic Achievement, Vocational Education, Standardized Tests, Foreign Countries
Shin, Tacksoo; Davison, Mark L.; Long, Jeffrey D. – Structural Equation Modeling: A Multidisciplinary Journal, 2009
The purpose of this study is to investigate the effects of missing data techniques in longitudinal studies under diverse conditions. A Monte Carlo simulation examined the performance of 3 missing data methods in latent growth modeling: listwise deletion (LD), maximum likelihood estimation using the expectation and maximization algorithm with a…
Descriptors: Sample Size, Monte Carlo Methods, Structural Equation Models, Data Collection
von Davier, Alina A.; Carstensen, Claus H.; von Davier, Matthias – ETS Research Report Series, 2006
Measuring and linking competencies require special instruments, special data collection designs, and special statistical models. The measurement instruments are tests or tests forms, which can be used in the following situations: The same test can be given repeatedly; two or more parallel tests forms (i.e., forms intended to be similar in…
Descriptors: Scores, Measurement Techniques, Competence, Comparative Analysis