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Saijun Zhao; Zhiyong Zhang; Hong Zhang – Grantee Submission, 2024
Mediation analysis is widely applied in various fields of science, such as psychology, epidemiology, and sociology. In practice, many psychological and behavioral phenomena are dynamic, and the corresponding mediation effects are expected to change over time. However, most existing mediation methods assume a static mediation effect over time,…
Descriptors: Bayesian Statistics, Statistical Inference, Longitudinal Studies, Attribution Theory
Saijun Zhao; Zhiyong Zhang; Hong Zhang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Mediation analysis is widely applied in various fields of science, such as psychology, epidemiology, and sociology. In practice, many psychological and behavioral phenomena are dynamic, and the corresponding mediation effects are expected to change over time. However, most existing mediation methods assume a static mediation effect over time,…
Descriptors: Bayesian Statistics, Statistical Inference, Longitudinal Studies, Attribution Theory
Jennifer Hill; George Perrett; Stacey A. Hancock; Le Win; Yoav Bergner – Statistics Education Research Journal, 2024
Most current statistics courses include some instruction relevant to causal inference. Whether this instruction is incorporated as material on randomized experiments or as an interpretation of associations measured by correlation or regression coefficients, the way in which this material is presented may have important implications for…
Descriptors: Statistics Education, Causal Models, Statistical Inference, College Students
Jennifer Hill; George Perrett; Stacey A. Hancock; Le Win; Yoav Bergner – Grantee Submission, 2024
Most current statistics courses include some instruction relevant to causal inference. Whether this instruction is incorporated as material on randomized experiments or as an interpretation of associations measured by correlation or regression coefficients, the way in which this material is presented may have important implications for…
Descriptors: Statistics Education, Teaching Methods, Attribution Theory, Undergraduate Students
Nathan McJames; Andrew Parnell; Ann O'Shea – Educational Review, 2025
Teacher shortages and attrition are problems of international concern. One of the most frequent reasons for teachers leaving the profession is a lack of job satisfaction. Accordingly, in this study we have adopted a causal inference machine learning approach to identify practical interventions for improving overall levels of job satisfaction. We…
Descriptors: Job Satisfaction, Teacher Surveys, Administrator Surveys, Faculty Mobility
Lu, Yonggang; Zheng, Qiujie; Quinn, Daniel – Journal of Statistics and Data Science Education, 2023
We present an instructional approach to teaching causal inference using Bayesian networks and "do"-Calculus, which requires less prerequisite knowledge of statistics than existing approaches and can be consistently implemented in beginner to advanced levels courses. Moreover, this approach aims to address the central question in causal…
Descriptors: Bayesian Statistics, Learning Motivation, Calculus, Advanced Courses
Puerta, Alejandro; Ramírez-Hassan, Andrés – Education Economics, 2022
We examine the effect of an integrity pilot campaign on undergraduates' behavior. As with many costly small-scale experiments and pilot programs, our statistical inference has to rely on small sample size. To tackle this issue, we perform a Bayesian retrospective power analysis. In our setup, a lecturer intentionally makes mistakes that favors…
Descriptors: Ethics, Integrity, Pilot Projects, Undergraduate Students
Peng Ding; Fan Li – Grantee Submission, 2018
Inferring causal effects of treatments is a central goal in many disciplines. The potential outcomes framework is a main statistical approach to causal inference, in which a causal effect is defined as a comparison of the potential outcomes of the same units under different treatment conditions. Because for each unit at most one of the potential…
Descriptors: Attribution Theory, Causal Models, Statistical Inference, Research Problems
Boyland, Lori – Planning and Changing, 2013
Due to an aging population of currently practicing superintendents, research predicts a large turnover in public school superintendent positions in this decade. Questions exist regarding whether there are sufficient numbers of potential superintendent candidates in training to fill these positions. Although principals have been recognized as a…
Descriptors: Superintendents, Principals, Administrator Attitudes, Public Schools
Foster, E. Michael – Developmental Psychology, 2010
Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether…
Descriptors: Psychologists, Risk, Family Structure, Regression (Statistics)
Dasinger, Jacob Arthur – Journal of Developmental Education, 2013
This research examined differences in causal attributions and an exam score in a developmental mathematics course based on student classification: traditional, minimally nontraditional, moderately nontraditional, and highly nontraditional as well as grade and gender among nontraditional students. Statistical analysis revealed significant…
Descriptors: Developmental Studies Programs, Remedial Mathematics, Student Characteristics, Gender Differences
Joshua, Monday T.; Joshua, Akon M. – Teacher Development, 2004
This study was designed to assess the attitudes of Nigerian secondary school teachers to student evaluation of teachers (SET), and to find out if the attitudes expressed were influenced by teacher characteristics such as gender, professional status, geographical location, academic qualification and teaching experience. The study was a survey, and…
Descriptors: Teacher Characteristics, Professional Recognition, Foreign Countries, Secondary School Teachers