Publication Date
In 2024 | 0 |
Since 2023 | 0 |
Since 2020 (last 5 years) | 0 |
Since 2015 (last 10 years) | 0 |
Since 2005 (last 20 years) | 2 |
Descriptor
Monte Carlo Methods | 4 |
Computation | 2 |
Effect Size | 2 |
Statistical Analysis | 2 |
Statistical Bias | 2 |
Academic Achievement | 1 |
Case Studies | 1 |
Comparative Analysis | 1 |
Computer Software | 1 |
Correlation | 1 |
Data Analysis | 1 |
More ▼ |
Source
Journal of Experimental… | 6 |
Author
Publication Type
Journal Articles | 6 |
Reports - Evaluative | 4 |
Reports - Research | 2 |
Education Level
Elementary Education | 1 |
Grade 3 | 1 |
Grade 4 | 1 |
Grade 5 | 1 |
Grade 6 | 1 |
Audience
Location
Taiwan | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Romano, Jeanine L.; Kromrey, Jeffrey D.; Owens, Corina M.; Scott, Heather M. – Journal of Experimental Education, 2011
In this study, the authors aimed to examine 8 of the different methods for computing confidence intervals around alpha that have been proposed to determine which of these, if any, is the most accurate and precise. Monte Carlo methods were used to simulate samples under known and controlled population conditions wherein the underlying item…
Descriptors: Intervals, Monte Carlo Methods, Rating Scales, Computation
Chen, Yi-Hsin; Thompson, Marilyn S.; Kromrey, Jeffrey D.; Chang, George H. – Journal of Experimental Education, 2011
In this article, the authors investigated the relations of students' perceptions of teachers' oral feedback with teacher expectancies and student self-concept. A sample of 1,598 Taiwanese children in Grades 3 to 6 completed measures of student perceptions of teacher oral feedback and school self-concept. Homeroom teachers identified students for…
Descriptors: Feedback (Response), Student Attitudes, Structural Equation Models, Discriminant Analysis
Peer reviewed
Kromrey, Jeffrey D.; Hines, Constance V. – Journal of Experimental Education, 1996
The accuracy of three analytical formulas for shrinkage estimation and four empirical techniques were investigated in a Monte Carlo study of the coefficient of cross-validity in multiple regression. Substantial statistical bias was evident for all techniques except the formula of M. W. Brown (1975) and multicross-validation. (SLD)
Descriptors: Estimation (Mathematics), Monte Carlo Methods, Regression (Statistics), Statistical Analysis
Peer reviewed
Ferron, John; Foster-Johnson, Lynn; Kromrey, Jeffrey D. – Journal of Experimental Education, 2003
Used Monte Carlo methods to examine the Type I error rates for randomization tests applied to single-case data arising from ABAB designs involving random, systematic, or response-guided assignment of interventions. Discusses conditions under which Type I error rate is controlled or is not. (SLD)
Descriptors: Error of Measurement, Monte Carlo Methods, Research Design
Peer reviewed
Kromrey, Jeffrey D.; Foster-Johnson, Lynn – Journal of Experimental Education, 1996
Presents use of the effect size as a descriptive statistic for single-subject research. Discusses the way in which effect sizes augment interpretation of results, and reviews four types of treatment effects with case studies. An appendix includes a sample computer program for computing effect sizes. (SLD)
Descriptors: Case Studies, Computer Software, Data Analysis, Effect Size
Peer reviewed
Kromrey, Jeffrey D.; La Rocca, Michela A. – Journal of Experimental Education, 1995
The Type I error rates and statistical power of nine selected multiple comparison procedures were compared in a Monte Carlo study. The Peretz, Ryan, and Fisher-Hayter tests were the most powerful, and differences among these procedures were consistently small. Choosing among these procedures might be based on their calculational complexity. (SLD)
Descriptors: Comparative Analysis, Computation, Monte Carlo Methods, Power (Statistics)