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Sangbaek Park – ProQuest LLC, 2024
This dissertation used synthetic datasets, semi-synthetic datasets, and a real-world dataset from an educational intervention to compare the performance of 15 machine learning and multiple imputation methods to estimate the individual treatment effect (ITE). In addition, it examined the performance of five evaluation metrics that can be used to…
Descriptors: Artificial Intelligence, Computation, Evaluation Methods, Bayesian Statistics
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
Peter Z. Schochet – Journal of Educational and Behavioral Statistics, 2025
Random encouragement designs evaluate treatments that aim to increase participation in a program or activity. These randomized controlled trials (RCTs) can also assess the mediated effects of participation itself on longer term outcomes using a complier average causal effect (CACE) estimation framework. This article considers power analysis…
Descriptors: Statistical Analysis, Computation, Causal Models, Research Design
Cody Ding – Educational Psychology Review, 2024
In the article "It's Just an Observation," Robinson and Wainer (Educational Psychology Review 35, Robinson, D., & Wainer, H. (2023). It's just an observation. Educational Psychology Review, 35(83), Published online: 14 August, 2023) lamented that educational psychology is moving toward the dark side of the quality continuum, with…
Descriptors: Journal Articles, Educational Psychology, Quality Assurance, Barriers
Bixi Zhang; Wolfgang Wiedermann – Society for Research on Educational Effectiveness, 2022
Background: Studying causal effects is an important aim in education. Causal relationships indicate how well implements (e.g., interventions) work for the target subjects. A good strategy to get the inference in such relationships is to conduct randomized experiments. However, random assignment is limited in education research, even is discouraged…
Descriptors: Statistical Analysis, Causal Models, Algorithms, Simulation
Heining Cham; Hyunjung Lee; Igor Migunov – Asia Pacific Education Review, 2024
The randomized control trial (RCT) is the primary experimental design in education research due to its strong internal validity for causal inference. However, in situations where RCTs are not feasible or ethical, quasi-experiments are alternatives to establish causal inference. This paper serves as an introduction to several quasi-experimental…
Descriptors: Causal Models, Educational Research, Quasiexperimental Design, Research Design
Nicholas D. Myers; Ahnalee M. Brincks; Seungmin Lee – Measurement in Physical Education and Exercise Science, 2024
Physical activity promotion is a best buy for public health because it has the potential to help individuals feel better, sleep better, and perform daily tasks more easily, in addition to providing disease prevention benefits. There is strong evidence that individual-level theory-based behavioral interventions are effective for increasing physical…
Descriptors: Physical Activity Level, Health Behavior, Health Promotion, Public Health
Adlof, Lauren; Kim, Minkyoung; Crawley, William – TechTrends: Linking Research and Practice to Improve Learning, 2023
Undergraduate student retention is considered a critical issue in higher education, due to its impact on student success, degree completion, and the financial health of universities (Cataldi et al., 2018; Cornelius & Cavanaugh, 2016; Hermes, "Community College Journal," 82(4), 26, 2012; Tinto, "NACADA Journal," 19(2), 5-9,…
Descriptors: Undergraduate Students, School Holding Power, Performance Technology, Academic Achievement
Nicholas D. Myers; Ahnalee M. Brincks; Seungmin Lee – Measurement in Physical Education and Exercise Science, 2025
Physical activity (PA) promotion is an ideal intervention target for public health because it has the potential to help individuals feel better, sleep better, and perform daily tasks more easily, in addition to providing disease prevention benefits. There is strong evidence that individual-level theory-based behavioral interventions are effective…
Descriptors: Physical Activity Level, Intervention, Program Effectiveness, Adults
Peter Schochet – Society for Research on Educational Effectiveness, 2024
Random encouragement designs are randomized controlled trials (RCTs) that test interventions aimed at increasing participation in a program or activity whose take up is not universal. In these RCTs, instead of randomizing individuals or clusters directly into treatment and control groups to participate in a program or activity, the randomization…
Descriptors: Statistical Analysis, Computation, Causal Models, Research Design
Vidushi Adlakha; Eric Kuo – Physical Review Physics Education Research, 2023
Recent critiques of physics education research (PER) studies have revoiced the critical issues when drawing causal inferences from observational data where no intervention is present. In response to a call for a "causal reasoning primer" in PER, this paper discusses some of the fundamental issues in statistical causal inference. In…
Descriptors: Physics, Science Education, Statistical Inference, Causal Models
Ha-Joon Chung; Guanglei Hong – Society for Research on Educational Effectiveness, 2024
Context: Prolonged disconnection from school and work represents major setbacks during the transition to adulthood and is a distinct feature of the developmental trajectories of many disadvantaged youths, especially those from a marginalized racial background (Hong and Chung 2022; Shanahan 2000). Differential schooling experiences are hypothesized…
Descriptors: Education Work Relationship, Racism, Disadvantaged, Student School Relationship
Xinxin Sun – Grantee Submission, 2023
Noncompliance to treatment assignment is widespread in randomized trials and presents challenges in causal inference. In the presence of noncompliance, the most commonly estimated effect of treatment assignment, also known as the intent-to-treat (ITT) effect, is biased. Of interest in this setting is the complier average causal effect (CACE), the…
Descriptors: Compliance (Psychology), Randomized Controlled Trials, Maximum Likelihood Statistics, Computation
Manolov, Rumen; Tanious, René; Fernández-Castilla, Belén – Journal of Applied Behavior Analysis, 2022
In science in general and in the context of single-case experimental designs, replication of the effects of the intervention within and/or across participants or experiments is crucial for establishing causality and for assessing the generality of the intervention effect. Specific developments and proposals for assessing whether an effect has been…
Descriptors: Intervention, Behavioral Science Research, Replication (Evaluation), Research Design
Deborah L. Hall; Yasin N. Silva; Brittany Wheeler; Lu Cheng; Katie Baumel – International Journal of Bullying Prevention, 2022
Cyberbullying has become increasingly prevalent, particularly on social media. There has also been a steady rise in cyberbullying research across a range of disciplines. Much of the empirical work from computer science has focused on developing machine learning models for cyberbullying detection. Whereas machine learning cyberbullying detection…
Descriptors: Bullying, Computer Mediated Communication, Social Media, Research