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Stephen Porter – Asia Pacific Education Review, 2024
Instrumental variables is a popular approach for causal inference in education when randomization of treatment is not feasible. Using a first-year college program as a running example, this article reviews the five assumptions that must be met to successfully use instrumental variables to estimate a causal effect with observational data: SUTVA,…
Descriptors: Causal Models, Educational Research, College Freshmen, Observation
Haixiang Zhang – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Mediation analysis is an important statistical tool in many research fields, where the joint significance test is widely utilized for examining mediation effects. Nevertheless, the limitation of this mediation testing method stems from its conservative Type I error, which reduces its statistical power and imposes certain constraints on its…
Descriptors: Structural Equation Models, Statistical Significance, Robustness (Statistics), Comparative Testing
Xiao Wen; Hu Juan – Interactive Learning Environments, 2024
To address three issues identified in previous research this study proposes a clustering-based MOOC dropout identification method and an early prediction model based on deep learning. The MOOC learning behavior of self-paced students was analyzed, and two well-known MOOC datasets were used for analysis and validation. The findings are as follows:…
Descriptors: MOOCs, Dropouts, Dropout Characteristics, Dropout Research
Sang-June Park; Youjae Yi – Journal of Educational and Behavioral Statistics, 2024
Previous research explicates ordinal and disordinal interactions through the concept of the "crossover point." This point is determined via simple regression models of a focal predictor at specific moderator values and signifies the intersection of these models. An interaction effect is labeled as disordinal (or ordinal) when the…
Descriptors: Interaction, Predictor Variables, Causal Models, Mathematical Models
Baker, Ryan S.; Esbenshade, Lief; Vitale, Jonathan; Karumbaiah, Shamya – Journal of Educational Data Mining, 2023
Predictive analytics methods in education are seeing widespread use and are producing increasingly accurate predictions of students' outcomes. With the increased use of predictive analytics comes increasing concern about fairness for specific subgroups of the population. One approach that has been proposed to increase fairness is using demographic…
Descriptors: Demography, Data Use, Prediction, Research Methodology
Marcinkowski, Tom; Reid, Alan – Environmental Education Research, 2019
Since the early days of the field, attitude-behavior (A-B) relationships have received sustained attention in the evaluation and researching of environmental education (EE). This level of interest extends beyond the field's scope though, in part due to a certain reliance on theoretical and empirical assertions which claim that attitudes serve as a…
Descriptors: Environmental Education, Attitudes, Behavior, Correlation
Ming-Chi Tseng – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The primary objective of this investigation is the formulation of random intercept latent profile transition analysis (RI-LPTA). Our simulation investigation suggests that the election between LPTA and RI-LPTA for examination has negligible impact on the estimation of transition probability parameters when the population parameters are generated…
Descriptors: Monte Carlo Methods, Predictor Variables, Research Methodology, Test Bias
Mizumoto, Atsushi – Language Learning, 2023
Researchers often make claims regarding the importance of predictor variables in multiple regression analysis by comparing standardized regression coefficients (standardized beta coefficients). This practice has been criticized as a misuse of multiple regression analysis. As a remedy, I highlight the use of dominance analysis and random forests, a…
Descriptors: Predictor Variables, Artificial Intelligence, Evaluation Methods, Multiple Regression Analysis
Bowden, Jack; Holmes, Michael V. – Research Synthesis Methods, 2019
Mendelian randomization (MR) uses genetic variants as instrumental variables to infer whether a risk factor causally affects a health outcome. Meta-analysis has been used historically in MR to combine results from separate epidemiological studies, with each study using a small but select group of genetic variants. In recent years, it has been used…
Descriptors: Meta Analysis, Research Design, Predictor Variables, Genetics
Archibald, John – Second Language Research, 2023
In this research note I want to address some misunderstandings about the construct of redeployment and suggest that we need to fit these behavioural data from Yang, Chen and Xiao (YCX) into a broader context. I will suggest that these authors' work is not just about the failure of three models to predict equivalence classification. Equivalence…
Descriptors: Phonology, Contrastive Linguistics, Mandarin Chinese, Russian
Young, Cristobal – Sociological Methods & Research, 2019
The commenter's proposal may be a reasonable method for addressing uncertainty in predictive modeling, where the goal is to predict "y." In a treatment effects framework, where the goal is causal inference by conditioning-on-observables, the commenter's proposal is deeply flawed. The proposal (1) ignores the definition of…
Descriptors: Causal Models, Predictor Variables, Research Methodology, Ambiguity (Context)
Turner, David A. – Compare: A Journal of Comparative and International Education, 2017
In his proposal for comparative education, Marc Antoinne Jullien de Paris argues that the comparative method offers a viable alternative to the experimental method. In an experiment, the scientist can manipulate the variables in such a way that he or she can see any possible combination of variables at will. In comparative education, or in…
Descriptors: Comparative Education, Comparative Analysis, Research Methodology, Predictor Variables
Stamovlasis, Dimitrios – Complicity: An International Journal of Complexity and Education, 2017
This paper discusses investigations in science education addressing the nonlinear dynamical hypothesis. Learning science is a suitable field for applying interdisciplinary research and predominately for testing psychological theories. It was demonstrated that in this area the paradigm of complexity and nonlinear dynamics have offered theoretical…
Descriptors: Science Education, Educational Research, Research Methodology, Predictor Variables
Williams, Tyreeka; Dowden, Angel – International Journal of the Whole Child, 2022
Prior to the COVID-19 pandemic, 44% of elementary-aged students reported experiencing adverse childhood experiences, while 13% reported experiencing three or more (Blodgett & Lanigan, 2018). During the COVID-19 pandemic, parents faced many hardships such as economic and health disparities. This resulted in an influx of reported and presumably…
Descriptors: Elementary School Students, Trauma, Early Experience, Child Neglect
Kaufman, James C. – Journal of Creative Behavior, 2017
This brief essay argues for the importance for more work on how creativity predicts positive outcomes, with a particular emphasis on expanding our definitions of these positive outcomes. The way that creativity may lead to increased equity and social justice is used as an example of these type of potential research questions.
Descriptors: Creativity, Social Justice, Predictor Variables, Definitions