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Benjamin M. Rottman; Yiwen Zhang – Cognitive Research: Principles and Implications, 2025
Being able to notice that a cause-effect relation is getting stronger or weaker is important for adapting to one's environment and deciding how to use the cause in the future. We conducted an experiment in which participants learned about a cause-effect relation that either got stronger or weaker over time. The experiment was conducted with a…
Descriptors: Causal Models, Memory, Learning Processes, Time
Sang Yoon Lee; Nicolas A. Roys; Ananth Seshadri – National Bureau of Economic Research, 2024
We present a model of endogenous schooling and earnings to isolate the causal effect of parents' education on children's education and earnings outcomes. The model suggests that parents' education is positively related to children's earnings, but its relationship with children's education is ambiguous. Identification is achieved by comparing the…
Descriptors: Parent Background, Educational Attainment, Correlation, Income
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Jason Schoeneberger; Christopher Rhoads – Grantee Submission, 2024
Regression discontinuity (RD) designs are increasingly used for causal evaluations. For example, if a student's need for a literacy intervention is determined by a low score on a past performance indicator and that intervention is provided to all students who fall below a cutoff on that indicator, an RD study can determine the intervention's main…
Descriptors: Regression (Statistics), Causal Models, Evaluation Methods, Multivariate Analysis
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Jason A. Schoeneberger; Christopher Rhoads – American Journal of Evaluation, 2025
Regression discontinuity (RD) designs are increasingly used for causal evaluations. However, the literature contains little guidance for conducting a moderation analysis within an RDD context. The current article focuses on moderation with a single binary variable. A simulation study compares: (1) different bandwidth selectors and (2) local…
Descriptors: Regression (Statistics), Causal Models, Evaluation Methods, Multivariate Analysis
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Kollin W. Rott; Gert Bronfort; Haitao Chu; Jared D. Huling; Brent Leininger; Mohammad Hassan Murad; Zhen Wang; James S. Hodges – Research Synthesis Methods, 2024
Meta-analysis is commonly used to combine results from multiple clinical trials, but traditional meta-analysis methods do not refer explicitly to a population of individuals to whom the results apply and it is not clear how to use their results to assess a treatment's effect for a population of interest. We describe recently-introduced causally…
Descriptors: Meta Analysis, Causal Models, Outcomes of Treatment, Medical Research
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Michal Shimonovich; Hilary Thomson; Anna Pearce; Srinivasa Vittal Katikireddi – Research Synthesis Methods, 2024
Background: Bradford Hill (BH) viewpoints are widely used to assess causality in systematic reviews, but their application has often lacked reproducibility. We describe an approach for assessing causality within systematic reviews ('causal' reviews), illustrating its application to the topic of income inequality and health. Our approach draws on…
Descriptors: Causal Models, Literature Reviews, Evaluation, Criteria
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Xiangyi Liao; Daniel M. Bolt; Jee-Seon Kim – Journal of Educational Measurement, 2024
Item difficulty and dimensionality often correlate, implying that unidimensional IRT approximations to multidimensional data (i.e., reference composites) can take a curvilinear form in the multidimensional space. Although this issue has been previously discussed in the context of vertical scaling applications, we illustrate how such a phenomenon…
Descriptors: Difficulty Level, Simulation, Multidimensional Scaling, Graphs
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Jie Ma; Wenyuan Wei – Journal of Creative Behavior, 2023
Curiosity has long been extolled as a seed for employee creativity. This causality is plausible when considering curiosity as a stable trait. However, curiosity can also oscillate as a transitory state, thus complicating the causal sequence between such state curiosity and creativity. To clarify the causal ordering and achieve a refined…
Descriptors: Personality Traits, Creativity, Employees, Reinforcement
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Chuenjai Sukpan; Rebecca M. Kuiper – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The (Random Intercept) Cross-Lagged Panel Model ((RI-)CLPM) is increasingly used in psychology and related fields to assess the longitudinal relationship of two or more variables on each other. Researchers are interested in the question which of the lagged effects is causally dominant receives considerable attention. However, currently used…
Descriptors: Causal Models, Psychological Studies, Multivariate Analysis, Cognitive Mapping
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Shikha N. Khera; Himanshu Pawar – Higher Education Quarterly, 2024
To date, student issues with Massive Open Online Courses (MOOCs) have only been explored in context-specific environments. Mainstream problems such as declining student motivation during a course, massive student dropout rates, accountability, user experience, etc., persist due to the permutations and combinations of these issues. Literature is…
Descriptors: MOOCs, Student Attitudes, Student Motivation, Dropout Rate
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Xiaotian Dai; Gareth J. Williams; John A. Groeger; Gary Jones; Keeley Brookes; Wei Zhou; Jing Hua; Wenchong Du – Autism: The International Journal of Research and Practice, 2025
Increasing evidence highlights the role of disrupted circadian rhythms in the neural dysfunctions and sleep disturbances observed in autism spectrum disorder and attention-deficit/hyperactivity disorder. However, the causality and directionality of these associations remain unclear. In this study, we employed a bidirectional two-sample Mendelian…
Descriptors: Foreign Countries, Autism Spectrum Disorders, Attention Deficit Hyperactivity Disorder, Sleep
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Alexander Robitzsch; Oliver Lüdtke – Structural Equation Modeling: A Multidisciplinary Journal, 2025
The random intercept cross-lagged panel model (RICLPM) decomposes longitudinal associations between two processes X and Y into stable between-person associations and temporal within-person changes. In a recent study, Bailey et al. demonstrated through a simulation study that the between-person variance components in the RICLPM can occur only due…
Descriptors: Longitudinal Studies, Correlation, Time, Simulation
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Rinthida Denphitat; Chintana Kanjanavisutt; Methinee Wongwanich Rumpagaporn – Higher Education Studies, 2025
The objective of this article is to develop a causal relationship factor model affecting entrepreneurial behavior for sustainable development using a mixed-methods research approach that integrated both quantitative and qualitative methodologies. The quantitative phase involved testing the causal relationships affecting entrepreneurial behavior by…
Descriptors: Causal Models, Entrepreneurship, Sustainable Development, Foreign Countries
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Rosa W. Runhardt – Sociological Methods & Research, 2024
This article uses the interventionist theory of causation, a counterfactual theory taken from philosophy of science, to strengthen causal analysis in process tracing research. Causal claims from process tracing are re-expressed in terms of so-called hypothetical interventions, and concrete evidential tests are proposed which are shown to…
Descriptors: Causal Models, Statistical Inference, Intervention, Investigations
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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
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