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W. Holmes Finch – Educational and Psychological Measurement, 2024
Dominance analysis (DA) is a very useful tool for ordering independent variables in a regression model based on their relative importance in explaining variance in the dependent variable. This approach, which was originally described by Budescu, has recently been extended to use with structural equation models examining relationships among latent…
Descriptors: Models, Regression (Statistics), Structural Equation Models, Predictor Variables
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Majid Ghasemy; James Eric Gaskin; James A. Elwood – Journal of Applied Research in Higher Education, 2024
Purpose: The direction of causality between job satisfaction and job performance (known as the holy grail of industrial psychologists) is undetermined and related research findings in different organizational contexts are mixed. Based on the ample literature, mainly from Western countries, on the relationship between job satisfaction and job…
Descriptors: Industrial Psychology, Models, Higher Education, Job Satisfaction
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Michael Kane – ETS Research Report Series, 2023
Linear functional relationships are intended to be symmetric and therefore cannot generally be accurately estimated using ordinary least squares regression equations. Orthogonal regression (OR) models allow for errors in both "Y" and "X" and therefore can provide symmetric estimates of these relationships. The most…
Descriptors: Factor Analysis, Regression (Statistics), Mathematical Models, Relationship
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Polat, Murat – Online Submission, 2023
This research focuses on better understanding the nature of pre-service teachers' four-frame leadership orientations. As it is known, the phenomenon of leadership still continues to be a research topic in the field of educational administration. But, these studies carried out on teachers and school administrators. As future teachers and school…
Descriptors: Preservice Teachers, Leadership Styles, Models, Gender Differences
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Taylor, John M. – Practical Assessment, Research & Evaluation, 2019
Although frequentist estimators can effectively fit ordinal confirmatory factor analysis (CFA) models, their assumptions are difficult to establish and estimation problems may prohibit their use at times. Consequently, researchers may want to also look to Bayesian analysis to fit their ordinal models. Bayesian methods offer researchers an…
Descriptors: Bayesian Statistics, Factor Analysis, Least Squares Statistics, Error of Measurement
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Kane, Michael T.; Mroch, Andrew A. – ETS Research Report Series, 2020
Ordinary least squares (OLS) regression and orthogonal regression (OR) address different questions and make different assumptions about errors. The OLS regression of Y on X yields predictions of a dependent variable (Y) contingent on an independent variable (X) and minimizes the sum of squared errors of prediction. It assumes that the independent…
Descriptors: Regression (Statistics), Least Squares Statistics, Test Bias, Error of Measurement
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Davis, Richard A. – Chemical Engineering Education, 2020
A case study of regression analysis based on modeling Gilliland's correlation was described for use in a computational methods course. The case study uses a familiar example to train students in nonlinear least squares regression and to use standardized residual plots for model assessment. Previously published equations for Gilliland's correlation…
Descriptors: Case Studies, Regression (Statistics), Correlation, Least Squares Statistics
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Kamdjou, Herve D. Teguim – Open Education Studies, 2023
This article revisits the Mincer earnings function and presents comparable estimates of the average monetary returns associated with an additional year of education across different regions worldwide. In contrast to the traditional Ordinary Least Squares (OLS) method commonly employed in the literature, this study applied a cutting-edge approach…
Descriptors: Outcomes of Education, Artificial Intelligence, Human Capital, Regression (Statistics)
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Picones, Gio; PaaBen, Benjamin; Koprinska, Irena; Yacef, Kalina – International Educational Data Mining Society, 2022
In this paper, we propose a novel approach to combine domain modelling and student modelling techniques in a single, automated pipeline which does not require expert knowledge and can be used to predict future student performance. Domain modelling techniques map questions to concepts and student modelling techniques generate a mastery score for a…
Descriptors: Prediction, Academic Achievement, Learning Analytics, Concept Mapping
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Aert, Robbie C. M.; Jackson, Dan – Research Synthesis Methods, 2019
The Hartung-Knapp method for random-effects meta-analysis, that was also independently proposed by Sidik and Jonkman, is becoming advocated for general use. This method has previously been justified by taking all estimated variances as known and using a different pivotal quantity to the more conventional one when making inferences about the…
Descriptors: Meta Analysis, Least Squares Statistics, Inferences, Guidelines
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Houcine, Benlaria; Sofiane, Mostéfaoui – Journal of Education and Training Studies, 2018
This study aims to measure the individual rate of return for investment in higher education at Adrar University by using both basic and extended Mincerian Earnings Function. In addition to this, the comparison had been established between the results obtained and those of other researches in the same domain. We adopted in the research the model of…
Descriptors: Foreign Countries, Higher Education, Outcomes of Education, Models
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DiStefano, Christine; McDaniel, Heather L.; Zhang, Liyun; Shi, Dexin; Jiang, Zhehan – Educational and Psychological Measurement, 2019
A simulation study was conducted to investigate the model size effect when confirmatory factor analysis (CFA) models include many ordinal items. CFA models including between 15 and 120 ordinal items were analyzed with mean- and variance-adjusted weighted least squares to determine how varying sample size, number of ordered categories, and…
Descriptors: Factor Analysis, Effect Size, Data, Sample Size
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Dougherty, Shaun M. – Journal of Education for Students Placed at Risk, 2018
Each iteration of high stakes accountability has included requirements to include measures of attendance in their accountability programs, thereby increasing the salience of this measure. Researchers too have turned to attendance and chronic absence as important outcomes in evaluations and policy studies. Often, too little attention is paid to the…
Descriptors: Attendance, Measurement, Models, Statistical Analysis
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Al-Emran, Mostafa; Teo, Timothy – Education and Information Technologies, 2020
Studying the factors that affect the e-learning adoption is not a new research topic. Nevertheless, exploring the effect of knowledge acquisition and knowledge sharing on e-learning adoption is a relatively new research trend that has not been featured in the existing literature. Thus, this study was conducted to build a new model by extending the…
Descriptors: Electronic Learning, Educational Technology, Information Technology, Technology Integration
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He, Tao; Zhu, Chang; Questier, Frederik – Asia Pacific Education Review, 2018
Although the adoption of digital technology has gained considerable attention in higher education, currently research mainly focuses on implementation in formal learning contexts. Investigating what factors influence students' digital informal learning is still unclear and limited. To understand better university students' digital informal…
Descriptors: College Students, Multimedia Materials, Electronic Publishing, Informal Education
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