Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 1 |
Since 2006 (last 20 years) | 4 |
Descriptor
Causal Models | 4 |
Probability | 4 |
Sample Size | 4 |
Effect Size | 2 |
Monte Carlo Methods | 2 |
Scores | 2 |
Simulation | 2 |
Statistical Bias | 2 |
Structural Equation Models | 2 |
Comparative Analysis | 1 |
Control Groups | 1 |
More ▼ |
Publication Type
Dissertations/Theses -… | 2 |
Journal Articles | 2 |
Reports - Descriptive | 1 |
Reports - Evaluative | 1 |
Education Level
Audience
Researchers | 1 |
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Beth A. Perkins – ProQuest LLC, 2021
In educational contexts, students often self-select into specific interventions (e.g., courses, majors, extracurricular programming). When students self-select into an intervention, systematic group differences may impact the validity of inferences made regarding the effect of the intervention. Propensity score methods are commonly used to reduce…
Descriptors: Probability, Causal Models, Evaluation Methods, Control Groups
Bellara, Aarti P. – ProQuest LLC, 2013
Propensity score analysis has been used to minimize the selection bias in observational studies to identify causal relationships. A propensity score is an estimate of an individual's probability of being placed in a treatment group given a set of covariates. Propensity score analysis aims to use the estimate to create balanced groups, akin to a…
Descriptors: Scores, Probability, Monte Carlo Methods, Statistical Analysis
Coffman, Donna L. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Mediation is usually assessed by a regression-based or structural equation modeling (SEM) approach that we refer to as the classical approach. This approach relies on the assumption that there are no confounders that influence both the mediator, "M", and the outcome, "Y". This assumption holds if individuals are randomly…
Descriptors: Structural Equation Models, Simulation, Regression (Statistics), Probability
Cheung, Mike W. L. – Structural Equation Modeling: A Multidisciplinary Journal, 2007
Mediators are variables that explain the association between an independent variable and a dependent variable. Structural equation modeling (SEM) is widely used to test models with mediating effects. This article illustrates how to construct confidence intervals (CIs) of the mediating effects for a variety of models in SEM. Specifically, mediating…
Descriptors: Structural Equation Models, Probability, Intervals, Sample Size