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T. D. Stanley; Hristos Doucouliagos; Tomas Havranek – Research Synthesis Methods, 2024
We demonstrate that all meta-analyses of partial correlations are biased, and yet hundreds of meta-analyses of partial correlation coefficients (PCCs) are conducted each year widely across economics, business, education, psychology, and medical research. To address these biases, we offer a new weighted average, UWLS[subscript +3]. UWLS[subscript…
Descriptors: Meta Analysis, Correlation, Bias, Sample Size
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Richard Breen; John Ermisch – Sociological Methods & Research, 2024
We consider the problem of bias arising from conditioning on a post-outcome collider. We illustrate this with reference to Elwert and Winship (2014) but we go beyond their study to investigate the extent to which inverse probability weighting might offer solutions. We use linear models to derive expressions for the bias arising in different kinds…
Descriptors: Probability, Statistical Bias, Weighted Scores, Least Squares Statistics
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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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Keefer, Quinn A. W. – Journal of Economic Education, 2023
An alternative approach for introducing instrumental variables in econometrics courses is presented in this article. The method is based on the ordinary least squares omitted variable bias formula. The intuition for the approach capitalizes on students' understanding and intuition of omitted variables. Thus, if students understand omitted variable…
Descriptors: Least Squares Statistics, Economics, Economics Education, Computation
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Jöran Petersson – International Journal of Mathematical Education in Science and Technology, 2024
Previous research has identified an unfilled gap between, on the one hand, mathematical prerequisites needed for a formal treatment of least squares and, on the other hand, only teaching procedural aspects of curve fitting. As a response to this, the present study explores students' suggestions of how they think a computer or calculator does curve…
Descriptors: Physics, Science Laboratories, Secondary School Students, Group Activities
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Ke-Hai Yuan; Zhiyong Zhang – Grantee Submission, 2022
Structural equation modeling (SEM) is a widely used technique for studies involving latent constructs. While covariance-based SEM (CB-SEM) permits estimating the regression relationship among latent constructs, the parameters governing this relationship do not apply to that among the scored values of the constructs, which are needed for…
Descriptors: Psychometrics, Structural Equation Models, Scores, Least Squares Statistics
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Ke-Hai Yuan; Yongfei Fang – Grantee Submission, 2023
Observational data typically contain measurement errors. Covariance-based structural equation modelling (CB-SEM) is capable of modelling measurement errors and yields consistent parameter estimates. In contrast, methods of regression analysis using weighted composites as well as a partial least squares approach to SEM facilitate the prediction and…
Descriptors: Structural Equation Models, Regression (Statistics), Weighted Scores, Comparative Analysis
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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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Rajesh Kumar Sharma; Sukhpreet Kaur – International Journal of Educational Management, 2024
Purpose: The purpose of this paper is to analyse the mediating role of organisational citizenship behaviour between transformational leadership and successful implementation of education 4.0 in higher educational institutes using the PLS-SEM approach. Design/methodology/approach: The study uses cross-sectional and quantitative approach to decode…
Descriptors: Transformational Leadership, Organizational Climate, Citizenship, Higher Education
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Avery H. Closser; Adam Sales; Anthony F. Botelho – Grantee Submission, 2024
Emergent technologies present platforms for educational researchers to conduct randomized controlled trials (RCTs) and collect rich data on study students' performance, behavior, learning processes, and outcomes in authentic learning environments. As educational research increasingly uses methods and data collection from such platforms, it is…
Descriptors: Data Analysis, Educational Research, Randomized Controlled Trials, Sampling
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Singh, Akansha; Uwimpuhwe, Germaine; Li, Mengchu; Einbeck, Jochen; Higgins, Steve; Kasim, Adetayo – International Journal of Research & Method in Education, 2022
In education, multisite trials involve randomization of pupils into intervention and comparison groups within schools. Most analytical models in multisite educational trials ignore that the impact of an intervention may be school dependent. This study investigates the impact of statistical models on the uncertainty associated with an effect size…
Descriptors: Randomized Controlled Trials, Effect Size, Hierarchical Linear Modeling, Least Squares Statistics
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Jalal, Azlin Abd; Hamid, Harris Shah Abd; Zulnaidi, Hutkemri – Malaysian Online Journal of Educational Sciences, 2023
In this new era drenched with data, statistical literacy becomes more essential for individuals to be able to read, communicate, and make informed decisions. Moreover, statistical literacy is highly essential for education policy makers who are highly accountable for all policy outcomes including school improvement, resource allocation, curriculum…
Descriptors: Statistics, Literacy, Educational Policy, Mathematics Anxiety
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Ghasemy, Majid; Teeroovengadum, Viraiyan; Becker, Jan-Michael; Ringle, Christian M. – Higher Education: The International Journal of Higher Education Research, 2020
The relevance and prominence of the partial least squares structural equation modeling (PLS-SEM) method has recently increased in higher education research, especially in explanatory and predictive studies. We therefore first aim to assess previous PLS-SEM applications by providing a systematic review; second, we aim to highlight and summarize…
Descriptors: Least Squares Statistics, Structural Equation Models, Higher Education, Educational Research
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Uanhoro, James O.; Wang, Yixi; O'Connell, Ann A. – Journal of Experimental Education, 2021
The standard regression technique for modeling binary response variables in education research is logistic regression. The odds ratios from these models are used to quantify and communicate variable effects. These effects are sometimes pooled together as in a meta-analysis. We argue that this process is problematic as odds ratios calculated from…
Descriptors: Probability, Effect Size, Regression (Statistics), Educational Research
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