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Sarah E. Robertson; Jon A. Steingrimsson; Issa J. Dahabreh – Evaluation Review, 2024
When planning a cluster randomized trial, evaluators often have access to an enumerated cohort representing the target population of clusters. Practicalities of conducting the trial, such as the need to oversample clusters with certain characteristics in order to improve trial economy or support inferences about subgroups of clusters, may preclude…
Descriptors: Randomized Controlled Trials, Generalization, Inferences, Hierarchical Linear Modeling
Xiaohui Luo; Yueqin Hu – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Intensive longitudinal data has been widely used to examine reciprocal or causal relations between variables. However, these variables may not be temporally aligned. This study examined the consequences and solutions of the problem of temporal misalignment in intensive longitudinal data based on dynamic structural equation models. First the impact…
Descriptors: Structural Equation Models, Longitudinal Studies, Data Analysis, Causal Models
Adam C. Sales; Ethan Prihar; Johann Gagnon-Bartsch; Ashish Gurung; Neil T. Heffernan – Grantee Submission, 2022
Randomized A/B tests allow causal estimation without confounding but are often under-powered. This paper uses a new dataset, including over 250 randomized comparisons conducted in an online learning platform, to illustrate a method combining data from A/B tests with log data from users who were not in the experiment. Inference remains exact and…
Descriptors: Research Methodology, Educational Experiments, Causal Models, Computation
Yi Feng; Peter M. Steiner – Society for Research on Educational Effectiveness, 2022
Research Context: In educational research, "context effects" are often of inferential interest to researchers as well as of evaluative interest to policymakers. While student education outcomes likely depend on individual-level influences like individual academic achievement, school contexts may also make a difference. Such questions are…
Descriptors: Hierarchical Linear Modeling, Accuracy, Graphs, Educational Research
Nyhout, Angela; Sweatman, Hilary; Ganea, Patricia A. – Child Development, 2023
Children's hypothetical reasoning about a complex and dynamic causal system was investigated. Predominantly White, middle-class 5- to 7-year-old children from the Greater Toronto Area learned about novel food chains and were asked to consider the effects of removing one species on the others. In Study 1 (N = 72; 36 females, 36 males; 2018),…
Descriptors: Childrens Attitudes, Thinking Skills, Causal Models, Systems Approach
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
Avery H. Closser; Adam Sales; Anthony F. Botelho – Educational Technology Research and Development, 2024
Emergent technologies present platforms for educational researchers to conduct randomized controlled trials (RCTs) and collect rich data to 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
Arel-Bundock, Vincent – Sociological Methods & Research, 2022
Qualitative comparative analysis (QCA) is an influential methodological approach motivated by set theory and boolean logic. QCA proponents have developed algorithms to analyze quantitative data, in a bid to uncover necessary and sufficient conditions where causal relationships are complex, conditional, or asymmetric. This article uses computer…
Descriptors: Comparative Analysis, Qualitative Research, Attribution Theory, Computer Simulation
Naccarato, Shawn L. – ProQuest LLC, 2019
A historic period of state divestment in public higher education, exacerbated by the "Great Recession" and attendant financial repercussions, has significantly altered public higher education financing. The most significant impact has been cost shift from the state to students via increasing tuition rates. These changes threaten student…
Descriptors: Predictor Variables, Alumni, Donors, Private Financial Support
Isaac M. Opper – Annenberg Institute for School Reform at Brown University, 2021
Researchers often include covariates when they analyze the results of randomized controlled trials (RCTs), valuing the increased precision of the estimates over the potential of inducing small-sample bias when doing so. In this paper, we develop a sufficient condition which ensures that the inclusion of covariates does not cause small-sample bias…
Descriptors: Randomized Controlled Trials, Sample Size, Statistical Bias, Artificial Intelligence
Cohausz, Lea – Journal of Educational Data Mining, 2022
Student success and drop-out predictions have gained increased attention in recent years, connected to the hope that by identifying struggling students, it is possible to intervene and provide early help and design programs based on patterns discovered by the models. Though by now many models exist achieving remarkable accuracy-values, models…
Descriptors: Guidelines, Academic Achievement, Dropouts, Prediction
Sibulkin, Amy E.; Butler, J. S. – Teaching of Psychology, 2019
After explicit instruction on how to give possible bidirectional (two-way) causality explanations for a correlation, 240 students from eight sections of social psychology and research methods courses wrote "reverse causality" explanations on various test questions, creating a total of 882 answers. Averaging across multiple graded…
Descriptors: Correlation, Causal Models, Research Methodology, Social Psychology
Edwards, Lynn Marie – ProQuest LLC, 2016
The purpose of the current study was to use a conceptual model to identify possible causal mechanisms at play in the phrase drill (PD) intervention. The study was carried out by isolating and investigating modeling and sentence repetition, which are two specific instructional components that are typically used in PD, by creating instructional…
Descriptors: Oral Reading, Drills (Practice), Reading Instruction, Sentences
Tang, Yang; Cook, Thomas D.; Kisbu-Sakarya, Yasemin – Society for Research on Educational Effectiveness, 2015
Regression discontinuity design (RD) has been widely used to produce reliable causal estimates. Researchers have validated the accuracy of RD design using within study comparisons (Cook, Shadish & Wong, 2008; Cook & Steiner, 2010; Shadish et al, 2011). Within study comparisons examines the validity of a quasi-experiment by comparing its…
Descriptors: Pretests Posttests, Statistical Bias, Accuracy, Regression (Statistics)
Porter, Kristin E.; Reardon, Sean F.; Unlu, Fatih; Bloom, Howard S.; Robinson-Cimpian, Joseph P. – MDRC, 2014
A valuable extension of the single-rating regression discontinuity design (RDD) is a multiple-rating RDD (MRRDD). To date, four main methods have been used to estimate average treatment effects at the multiple treatment frontiers of an MRRDD: the "surface" method, the "frontier" method, the "binding-score" method, and…
Descriptors: Regression (Statistics), Research Design, Quasiexperimental Design, Research Methodology
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