Publication Date
In 2025 | 1 |
Since 2024 | 4 |
Since 2021 (last 5 years) | 6 |
Descriptor
Bayesian Statistics | 6 |
Mathematical Formulas | 6 |
Structural Equation Models | 3 |
Accuracy | 2 |
Computation | 2 |
Data Analysis | 2 |
Error of Measurement | 2 |
Goodness of Fit | 2 |
Matrices | 2 |
Sample Size | 2 |
Simulation | 2 |
More ▼ |
Author
Dongho Shin | 1 |
Guo, Xiaojun | 1 |
Haiyan Liu | 1 |
Han Du | 1 |
Hao Wu | 1 |
Li, Yujun | 1 |
Lijuan Wang | 1 |
Luo, Guanzhong | 1 |
Luo, Zhaosheng | 1 |
Lydia Marvin | 1 |
Mauricio Garnier-Villarreal | 1 |
More ▼ |
Publication Type
Reports - Research | 6 |
Journal Articles | 5 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Dongho Shin; Yongyun Shin; Nao Hagiwara – Grantee Submission, 2025
We consider Bayesian estimation of a hierarchical linear model (HLM) from partially observed data, assumed to be missing at random, and small sample sizes. A vector of continuous covariates C includes cluster-level partially observed covariates with interaction effects. Due to small sample sizes from 37 patient-physician encounters repeatedly…
Descriptors: Bayesian Statistics, Hierarchical Linear Modeling, Multivariate Analysis, Data Analysis
Mauricio Garnier-Villarreal; Terrence D. Jorgensen – Grantee Submission, 2024
Model evaluation is a crucial step in SEM, consisting of two broad areas: global and local fit, where local fit indices are use to modify the original model. In the modification process, the modification index (MI) and the standardized expected parameter change (SEPC) are used to select the parameters that can be added to improve the fit. The…
Descriptors: Bayesian Statistics, Structural Equation Models, Goodness of Fit, Indexes
Han Du; Hao Wu – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Real data are unlikely to be exactly normally distributed. Ignoring non-normality will cause misleading and unreliable parameter estimates, standard error estimates, and model fit statistics. For non-normal data, researchers have proposed a distributionally-weighted least squares (DLS) estimator to combines the normal theory based generalized…
Descriptors: Least Squares Statistics, Matrices, Statistical Distributions, Bayesian Statistics
Xiao Liu; Lijuan Wang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
In parallel process latent growth curve mediation models, the mediation pathways from treatment to the intercept or slope of outcome through the intercept or slope of mediator are often of interest. In this study, we developed causal mediation analysis methods for these mediation pathways. Particularly, we provided causal definitions and…
Descriptors: Causal Models, Mediation Theory, Psychological Studies, Educational Research
Shu, Tian; Luo, Guanzhong; Luo, Zhaosheng; Yu, Xiaofeng; Guo, Xiaojun; Li, Yujun – Journal of Educational and Behavioral Statistics, 2023
Cognitive diagnosis models (CDMs) are the statistical framework for cognitive diagnostic assessment in education and psychology. They generally assume that subjects' latent attributes are dichotomous--mastery or nonmastery, which seems quite deterministic. As an alternative to dichotomous attribute mastery, attention is drawn to the use of a…
Descriptors: Cognitive Measurement, Models, Diagnostic Tests, Accuracy
Haiyan Liu; Sarah Depaoli; Lydia Marvin – Structural Equation Modeling: A Multidisciplinary Journal, 2022
The deviance information criterion (DIC) is widely used to select the parsimonious, well-fitting model. We examined how priors impact model complexity (pD) and the DIC for Bayesian CFA. Study 1 compared the empirical distributions of pD and DIC under multivariate (i.e., inverse Wishart) and separation strategy (SS) priors. The former treats the…
Descriptors: Structural Equation Models, Bayesian Statistics, Goodness of Fit, Factor Analysis