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) | 4 |
Descriptor
Computer Software | 6 |
Simulation | 5 |
Item Response Theory | 3 |
Computation | 2 |
Data Analysis | 2 |
Factor Analysis | 2 |
Foreign Countries | 2 |
Hypothesis Testing | 2 |
Mathematics | 2 |
Sample Size | 2 |
Statistical Analysis | 2 |
More ▼ |
Source
Journal of Educational and… | 6 |
Author
Browne, William | 1 |
Cai, Li | 1 |
Charlton, Chris | 1 |
French, Robert | 1 |
Hayes, Andrew F. | 1 |
Leckie, George | 1 |
Lee, John C. K. | 1 |
Lee, Sik-Yum | 1 |
Segawa, Eisuke | 1 |
Sinharay, Sandip | 1 |
Song, Xin-Yuan | 1 |
More ▼ |
Publication Type
Journal Articles | 6 |
Reports - Research | 3 |
Reports - Descriptive | 2 |
Reports - Evaluative | 1 |
Education Level
Secondary Education | 1 |
Audience
Location
Hong Kong | 1 |
Laws, Policies, & Programs
Assessments and Surveys
Program for International… | 1 |
What Works Clearinghouse Rating
Yang, Ji Seung; Zheng, Xiaying – Journal of Educational and Behavioral Statistics, 2018
The purpose of this article is to introduce and review the capability and performance of the Stata item response theory (IRT) package that is available from Stata v.14, 2015. Using a simulated data set and a publicly available item response data set extracted from Programme of International Student Assessment, we review the IRT package from…
Descriptors: Item Response Theory, Item Analysis, Computer Software, Statistical Analysis
Leckie, George; French, Robert; Charlton, Chris; Browne, William – Journal of Educational and Behavioral Statistics, 2014
Applications of multilevel models to continuous outcomes nearly always assume constant residual variance and constant random effects variances and covariances. However, modeling heterogeneity of variance can prove a useful indicator of model misspecification, and in some educational and behavioral studies, it may even be of direct substantive…
Descriptors: Hierarchical Linear Modeling, Statistical Analysis, Predictor Variables, Computer Software
Cai, Li; Hayes, Andrew F. – Journal of Educational and Behavioral Statistics, 2008
When the errors in an ordinary least squares (OLS) regression model are heteroscedastic, hypothesis tests involving the regression coefficients can have Type I error rates that are far from the nominal significance level. Asymptotically, this problem can be rectified with the use of a heteroscedasticity-consistent covariance matrix (HCCM)…
Descriptors: Least Squares Statistics, Error Patterns, Error Correction, Computation
von Davier, Matthias; Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2007
Reporting methods used in large-scale assessments such as the National Assessment of Educational Progress (NAEP) rely on latent regression models. To fit the latent regression model using the maximum likelihood estimation technique, multivariate integrals must be evaluated. In the computer program MGROUP used by the Educational Testing Service for…
Descriptors: Simulation, Computer Software, Sampling, Data Analysis
Lee, Sik-Yum; Song, Xin-Yuan; Lee, John C. K. – Journal of Educational and Behavioral Statistics, 2003
The existing maximum likelihood theory and its computer software in structural equation modeling are established on the basis of linear relationships among latent variables with fully observed data. However, in social and behavioral sciences, nonlinear relationships among the latent variables are important for establishing more meaningful models…
Descriptors: Structural Equation Models, Simulation, Computer Software, Computation
Segawa, Eisuke – Journal of Educational and Behavioral Statistics, 2005
Multi-indicator growth models were formulated as special three-level hierarchical generalized linear models to analyze growth of a trait latent variable measured by ordinal items. Items are nested within a time-point, and time-points are nested within subject. These models are special because they include factor analytic structure. This model can…
Descriptors: Bayesian Statistics, Mathematical Models, Factor Analysis, Computer Simulation