NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 74 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Philipp Sterner; Florian Pargent; Dominik Deffner; David Goretzko – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Measurement invariance (MI) describes the equivalence of measurement models of a construct across groups or time. When comparing latent means, MI is often stated as a prerequisite of meaningful group comparisons. The most common way to investigate MI is multi-group confirmatory factor analysis (MG-CFA). Although numerous guides exist, a recent…
Descriptors: Structural Equation Models, Causal Models, Measurement, Predictor Variables
Peer reviewed Peer reviewed
Direct linkDirect link
Steffen Erickson – Society for Research on Educational Effectiveness, 2024
Background: Structural Equation Modeling (SEM) is a powerful and broadly utilized statistical framework. Researchers employ these models to dissect relationships into direct, indirect, and total effects (Bollen, 1989). These models unpack the "black box" issues within cause-and-effect studies by examining the underlying theoretical…
Descriptors: Structural Equation Models, Causal Models, Research Methodology, Error of Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
Xiao Liu; Lijuan Wang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
In parallel process latent growth curve mediation models, the mediation pathways from treatment to the intercept or slope of outcome through the intercept or slope of mediator are often of interest. In this study, we developed causal mediation analysis methods for these mediation pathways. Particularly, we provided causal definitions and…
Descriptors: Causal Models, Mediation Theory, Psychological Studies, Educational Research
Peer reviewed Peer reviewed
Direct linkDirect link
Xiaohui Luo; Yueqin Hu – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Intensive longitudinal data has been widely used to examine reciprocal or causal relations between variables. However, these variables may not be temporally aligned. This study examined the consequences and solutions of the problem of temporal misalignment in intensive longitudinal data based on dynamic structural equation models. First the impact…
Descriptors: Structural Equation Models, Longitudinal Studies, Data Analysis, Causal Models
Peer reviewed Peer reviewed
Direct linkDirect link
Ruoxuan Li; Lijuan Wang – Grantee Submission, 2024
Causal-formative indicators are often used in social science research. To achieve identification in causal-formative indicator modeling, constraints need to be applied. A conventional method is to constrain the weight of a formative indicator to be 1. The selection of which indicator to have the fixed weight, however, may influence statistical…
Descriptors: Social Science Research, Causal Models, Formative Evaluation, Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
Dae Woong Ham; Luke Miratrix – Grantee Submission, 2024
The consequence of a change in school leadership (e.g., principal turnover) on student achievement has important implications for education policy. The impact of such an event can be estimated via the popular Difference in Difference (DiD) estimator, where those schools with a turnover event are compared to a selected set of schools that did not…
Descriptors: Trend Analysis, Faculty Mobility, Academic Achievement, Principals
Peer reviewed Peer reviewed
Direct linkDirect link
Yangqiuting Li; Chandralekha Singh – Physical Review Physics Education Research, 2024
Structural equation modeling (SEM) is a statistical method widely used in educational research to investigate relationships between variables. SEM models are typically constructed based on theoretical foundations and assessed through fit indices. However, a well-fitting SEM model alone is not sufficient to verify the causal inferences underlying…
Descriptors: Structural Equation Models, Statistical Analysis, Educational Research, Causal Models
Peer reviewed Peer reviewed
Direct linkDirect link
Ke-Hai Yuan; Zhiyong Zhang; Lijuan Wang – Grantee Submission, 2024
Mediation analysis plays an important role in understanding causal processes in social and behavioral sciences. While path analysis with composite scores was criticized to yield biased parameter estimates when variables contain measurement errors, recent literature has pointed out that the population values of parameters of latent-variable models…
Descriptors: Structural Equation Models, Path Analysis, Weighted Scores, Comparative Testing
Peer reviewed Peer reviewed
Direct linkDirect link
Zeynivandnezhad, Fereshteh; Asgharzadeh, Nasrin; Fernández, Ramón Emilio – International Journal for Technology in Mathematics Education, 2023
The applicability of digital technologies is increasing boundlessly and so are the opportunities of the end-users, with ample opportunities to embed these technologies in the teaching and learning process. Nonetheless, classroom adoption of technologies, particularly in mathematics remains on the lower end of innovation in teaching and learning.…
Descriptors: Foreign Countries, High Schools, Mathematics Teachers, Pedagogical Content Knowledge
Petscher, Yaacov; Schatschneider, Christopher – Educational and Psychological Measurement, 2019
Complex data structures are ubiquitous in psychological research, especially in educational settings. In the context of randomized controlled trials, students are nested in classrooms but may be cross-classified by other units, such as small groups. Furthermore, in many cases only some students may be nested within a unit while other students may…
Descriptors: Structural Equation Models, Causal Models, Randomized Controlled Trials, Hierarchical Linear Modeling
Petscher, Yaacov; Schatschneider, Christopher – Grantee Submission, 2019
Complex data structures are ubiquitous in psychological research, especially in educational settings. In the context of randomized controlled trials, students are nested in classrooms but may be cross-classified by other units, such as small groups. Further, in many cases only some students may be nested within a unit while other students may not.…
Descriptors: Structural Equation Models, Causal Models, Randomized Controlled Trials, Hierarchical Linear Modeling
Peer reviewed Peer reviewed
Direct linkDirect link
Gibbons, Rebecca E.; Xu, Xiaoying; Villafañe, Sachel M.; Raker, Jeffrey R. – Educational Psychology, 2018
Affective factors such as the achievement emotions are considered critical for students' academic performance in STEM degree programmes and careers. In this study, a reciprocal causation model was tested between two affective factors: enjoyment and anxiety, and organic chemistry course performance. Each variable was measured three times in four…
Descriptors: Causal Models, Affective Behavior, Psychological Patterns, Anxiety
Peer reviewed Peer reviewed
Direct linkDirect link
Zhao, Yu; Lei, Pui-Wa – AERA Online Paper Repository, 2016
Despite the prevalence of ordinal observed variables in applied structural equation modeling (SEM) research, limited attention has been given to model evaluation methods suitable for ordinal variables, thus providing practitioners in the field with few guidelines to follow. This study represents a first attempt to thoroughly examine the…
Descriptors: Factor Analysis, Monte Carlo Methods, Causal Models, Least Squares Statistics
Peer reviewed Peer reviewed
Direct linkDirect link
Castellano, Marisa E.; Richardson, George B.; Sundell, Kirsten; Stone, James R., III – Vocations and Learning, 2017
In the United States, education policy calls for every student to graduate from high school prepared for college and a career. National legislation has mandated programs of study (POS), which offer aligned course sequences spanning secondary and postsecondary education, blending standards-based academic and career and technical education (CTE)…
Descriptors: College Preparation, College Readiness, Career Development, Career Readiness
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Pérez, Andrea; Collado, Jesús; del Mar García de los Salmones, María; Herrero, Ángel; San Martín, Héctor – Journal of the Scholarship of Teaching and Learning, 2019
This paper explores a causal model, using Structural Equation Modelling (SEM), in order to understand how the perceived effectiveness of the 'flipped classroom' and students' satisfaction with this technique can be affected by students' engagement in the 'flipped classroom' activities as well as the complexity and task orientation of such…
Descriptors: Instructional Effectiveness, Business Communication, Causal Models, Student Satisfaction
Previous Page | Next Page »
Pages: 1  |  2  |  3  |  4  |  5