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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
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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
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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
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Ellison, George T. H. – Journal of Statistics and Data Science Education, 2021
Temporality-driven covariate classification had limited impact on: the specification of directed acyclic graphs (DAGs) by 85 novice analysts (medical undergraduates); or the risk of bias in DAG-informed multivariable models designed to generate causal inference from observational data. Only 71 students (83.5%) managed to complete the…
Descriptors: Statistics Education, Medical Education, Undergraduate Students, Graphs
Xinran Li; Peng Ding – Grantee Submission, 2018
Frequentists' inference often delivers point estimators associated with confidence intervals or sets for parameters of interest. Constructing the confidence intervals or sets requires understanding the sampling distributions of the point estimators, which, in many but not all cases, are related to asymptotic Normal distributions ensured by central…
Descriptors: Correlation, Intervals, Sampling, Evaluation Methods
Gagnon-Bartsch, J. A.; Sales, A. C.; Wu, E.; Botelho, A. F.; Erickson, J. A.; Miratrix, L. W.; Heffernan, N. T. – Grantee Submission, 2019
Randomized controlled trials (RCTs) admit unconfounded design-based inference--randomization largely justifies the assumptions underlying statistical effect estimates--but often have limited sample sizes. However, researchers may have access to big observational data on covariates and outcomes from RCT non-participants. For example, data from A/B…
Descriptors: Randomized Controlled Trials, Educational Research, Prediction, Algorithms
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Wiedermann, Wolfgang; von Eye, Alexander – International Journal of Behavioral Development, 2015
The concept of direction dependence has attracted growing attention due to its potential to help decide which of two competing linear regression models (X ? Y or Y ? X) is more likely to reflect the correct causal flow. Several tests have been proposed to evaluate hypotheses compatible with direction dependence. In this issue, Thoemmes (2015)…
Descriptors: Regression (Statistics), Correlation, Influences, Predictor Variables
Imbens, Guido W.; Rubin, Donald B. – Cambridge University Press, 2015
Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding…
Descriptors: Causal Models, Statistical Inference, Statistics, Social Sciences