Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 1 |
Since 2006 (last 20 years) | 2 |
Descriptor
Error Correction | 3 |
Error Patterns | 3 |
Monte Carlo Methods | 3 |
Evaluation Methods | 2 |
Sample Size | 2 |
Statistical Bias | 2 |
Computation | 1 |
Correlation | 1 |
Effect Size | 1 |
Evaluation Research | 1 |
Intervals | 1 |
More ▼ |
Publication Type
Journal Articles | 2 |
Dissertations/Theses -… | 1 |
Reports - Evaluative | 1 |
Reports - Research | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Leth-Steensen, Craig; Gallitto, Elena – Educational and Psychological Measurement, 2016
A large number of approaches have been proposed for estimating and testing the significance of indirect effects in mediation models. In this study, four sets of Monte Carlo simulations involving full latent variable structural equation models were run in order to contrast the effectiveness of the currently popular bias-corrected bootstrapping…
Descriptors: Mediation Theory, Structural Equation Models, Monte Carlo Methods, Simulation
Garrett, Phyllis – ProQuest LLC, 2009
The use of polytomous items in assessments has increased over the years, and as a result, the validity of these assessments has been a concern. Differential item functioning (DIF) and missing data are two factors that may adversely affect assessment validity. Both factors have been studied separately, but DIF and missing data are likely to occur…
Descriptors: Sample Size, Monte Carlo Methods, Test Validity, Effect Size
Chan, Wai; Chan, Daniel W.-L. – Psychological Methods, 2004
The standard Pearson correlation coefficient is a biased estimator of the true population correlation, ?, when the predictor and the criterion are range restricted. To correct the bias, the correlation corrected for range restriction, r-sub(c), has been recommended, and a standard formula based on asymptotic results for estimating its standard…
Descriptors: Computation, Intervals, Sample Size, Monte Carlo Methods