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Showing 1 to 15 of 29 results Save | Export
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James Ohisei Uanhoro – Educational and Psychological Measurement, 2024
Accounting for model misspecification in Bayesian structural equation models is an active area of research. We present a uniquely Bayesian approach to misspecification that models the degree of misspecification as a parameter--a parameter akin to the correlation root mean squared residual. The misspecification parameter can be interpreted on its…
Descriptors: Bayesian Statistics, Structural Equation Models, Simulation, Statistical Inference
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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
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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
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Xu, Menglin; Logan, Jessica A. R. – Journal of Research on Educational Effectiveness, 2021
Planned missing data designs allow researchers to have highly-powered studies by testing only a fraction of the traditional sample size. In two-method measurement planned missingness designs, researchers assess only part of the sample on a high-quality expensive measure, while the entire sample is given a more inexpensive, but biased measure. The…
Descriptors: Longitudinal Studies, Research Design, Research Problems, Structural Equation Models
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Mansolf, Maxwell; Jorgensen, Terrence D.; Enders, Craig K. – Grantee Submission, 2020
Structural equation modeling (SEM) applications routinely employ a trilogy of significance tests that includes the likelihood ratio test, Wald test, and score test or modification index. Researchers use these tests to assess global model fit, evaluate whether individual estimates differ from zero, and identify potential sources of local misfit,…
Descriptors: Structural Equation Models, Computation, Scores, Simulation
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Devlieger, Ines; Talloen, Wouter; Rosseel, Yves – Educational and Psychological Measurement, 2019
Factor score regression (FSR) is a popular alternative for structural equation modeling. Naively applying FSR induces bias for the estimators of the regression coefficients. Croon proposed a method to correct for this bias. Next to estimating effects without bias, interest often lies in inference of regression coefficients or in the fit of the…
Descriptors: Regression (Statistics), Computation, Goodness of Fit, Statistical Inference
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Chung, Seungwon; Cai, Li – Grantee Submission, 2019
The use of item responses from questionnaire data is ubiquitous in social science research. One side effect of using such data is that researchers must often account for item level missingness. Multiple imputation (Rubin, 1987) is one of the most widely used missing data handling techniques. The traditional multiple imputation approach in…
Descriptors: Computation, Statistical Inference, Structural Equation Models, Goodness of Fit
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Bai, Haiyan; Sivo, Stephen A.; Pan, Wei; Fan, Xitao – International Journal of Research & Method in Education, 2016
Among the commonly used resampling methods of dealing with small-sample problems, the bootstrap enjoys the widest applications because it often outperforms its counterparts. However, the bootstrap still has limitations when its operations are contemplated. Therefore, the purpose of this study is to examine an alternative, new resampling method…
Descriptors: Sampling, Structural Equation Models, Statistical Inference, Comparative Analysis
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Valente, Matthew J.; Gonzalez, Oscar; Miocevic, Milica; MacKinnon, David P. – Educational and Psychological Measurement, 2016
Methods to assess the significance of mediated effects in education and the social sciences are well studied and fall into two categories: single sample methods and computer-intensive methods. A popular single sample method to detect the significance of the mediated effect is the test of joint significance, and a popular computer-intensive method…
Descriptors: Structural Equation Models, Sampling, Statistical Inference, Statistical Bias
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Kio, Su Iong; Lau, Meng Chan Virgina – Education and Information Technologies, 2017
The study builds on a newly modified Technology Acceptance Model (TAM) to substantiate the motivation and operation of teachers' utilization of online learning resources. A "Comprehensiveness" construct is proposed in the modified TAM to reflect the breadth and depth of rich online knowledge. This new construct serves as the mediator…
Descriptors: Electronic Learning, Educational Resources, Foreign Countries, Structural Equation Models
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Ibrahim, Mikail; Baharun, Hazleena; Harun, Haliza; Othman, Normah – Malaysian Journal of Learning and Instruction, 2017
Purpose: This study examined the interrelationships between a set of antecedent academic intrinsic motivations and metacognitive strategy such as goal orientation, perceived value and religiosity in Fundamental Knowledge for Matriculation courses (FKM). It also investigated the relationship between intrinsic motivation and metacognitive strategy…
Descriptors: Motivation, Metacognition, Academic Achievement, College Students
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Leth-Steensen, Craig; Gallitto, Elena – Educational and Psychological Measurement, 2016
A large number of approaches have been proposed for estimating and testing the significance of indirect effects in mediation models. In this study, four sets of Monte Carlo simulations involving full latent variable structural equation models were run in order to contrast the effectiveness of the currently popular bias-corrected bootstrapping…
Descriptors: Mediation Theory, Structural Equation Models, Monte Carlo Methods, Simulation
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Meng, Qian; Zhu, Chang; Cao, Chun – Higher Education: The International Journal of Higher Education Research, 2018
This study examined global competence of Chinese international students sojourning in a non-Anglophone European country as a mediator between foreign language proficiency (i.e., English and local language) and social and academic adaptation, and social connectedness in international community. A sample of 206 Chinese students in Belgium responded…
Descriptors: Foreign Students, Interpersonal Relationship, Social Adjustment, Student Adjustment
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Levy, Roy – Educational Psychologist, 2016
In this article, I provide a conceptually oriented overview of Bayesian approaches to statistical inference and contrast them with frequentist approaches that currently dominate conventional practice in educational research. The features and advantages of Bayesian approaches are illustrated with examples spanning several statistical modeling…
Descriptors: Bayesian Statistics, Models, Educational Research, Innovation
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Yoon, Jae ho; Lee, Ji hae; Lee, Chae Yeon; Cho, Minhee; Lee, Sang Min – Asia Pacific Education Review, 2014
The purpose of the current study is to demonstrate a significant suppressor effect among coping strategies on resilience. Two different samples were used to replicate the suppressor effect. Participants in the first example were 391 adolescents (middle school students) in Korea, and participants in the second example were 282 young adults…
Descriptors: Foreign Countries, Coping, Resilience (Psychology), Adolescents
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