Publication Date
In 2025 | 0 |
Since 2024 | 3 |
Since 2021 (last 5 years) | 5 |
Since 2016 (last 10 years) | 6 |
Since 2006 (last 20 years) | 6 |
Descriptor
Bayesian Statistics | 6 |
Growth Models | 6 |
Statistical Inference | 6 |
Monte Carlo Methods | 3 |
Maximum Likelihood Statistics | 2 |
Mediation Theory | 2 |
Robustness (Statistics) | 2 |
Academic Achievement | 1 |
Algorithms | 1 |
Classification | 1 |
Correlation | 1 |
More ▼ |
Source
Structural Equation Modeling:… | 2 |
Educational and Psychological… | 1 |
Grantee Submission | 1 |
Journal of Educational and… | 1 |
School Effectiveness and… | 1 |
Author
Kristin Valentino | 2 |
Lijuan Wang | 2 |
Xiao Liu | 2 |
Zhiyong Zhang | 2 |
David Kaplan | 1 |
Guerra-Peña, Kiero | 1 |
Harring, Jeffrey R. | 1 |
Kjorte Harra | 1 |
Lee, Daniel Y. | 1 |
Levy, Roy | 1 |
Liu, Yixing | 1 |
More ▼ |
Publication Type
Journal Articles | 6 |
Reports - Research | 5 |
Reports - Evaluative | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Xiao Liu; Zhiyong Zhang; Kristin Valentino; Lijuan Wang – Grantee Submission, 2024
Parallel process latent growth curve mediation models (PP-LGCMMs) are frequently used to longitudinally investigate the mediation effects of treatment on the level and change of outcome through the level and change of mediator. An important but often violated assumption in empirical PP-LGCMM analysis is the absence of omitted confounders of the…
Descriptors: Mediation Theory, Bayesian Statistics, Growth Models, Monte Carlo Methods
Xiao Liu; Zhiyong Zhang; Kristin Valentino; Lijuan Wang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Parallel process latent growth curve mediation models (PP-LGCMMs) are frequently used to longitudinally investigate the mediation effects of treatment on the level and change of outcome through the level and change of mediator. An important but often violated assumption in empirical PP-LGCMM analysis is the absence of omitted confounders of the…
Descriptors: Mediation Theory, Bayesian Statistics, Growth Models, Monte Carlo Methods
Kjorte Harra; David Kaplan – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The present work focuses on the performance of two types of shrinkage priors--the horseshoe prior and the recently developed regularized horseshoe prior--in the context of inducing sparsity in path analysis and growth curve models. Prior research has shown that these horseshoe priors induce sparsity by at least as much as the "gold…
Descriptors: Structural Equation Models, Bayesian Statistics, Regression (Statistics), Statistical Inference
Lee, Daniel Y.; Harring, Jeffrey R. – Journal of Educational and Behavioral Statistics, 2023
A Monte Carlo simulation was performed to compare methods for handling missing data in growth mixture models. The methods considered in the current study were (a) a fully Bayesian approach using a Gibbs sampler, (b) full information maximum likelihood using the expectation-maximization algorithm, (c) multiple imputation, (d) a two-stage multiple…
Descriptors: Monte Carlo Methods, Research Problems, Statistical Inference, Bayesian Statistics
Liu, Yixing; Levy, Roy; Yel, Nedim; Schulte, Ann C. – School Effectiveness and School Improvement, 2023
Although there is recognition that there may be differential outcomes for groups of students within schools, examination of outcomes for subgroups presents challenges to researchers and policymakers. It complicates analytic procedures, particularly when the number of students per school in the subgroup is small. We explored five alternatives for…
Descriptors: Growth Models, Hierarchical Linear Modeling, School Effectiveness, Academic Achievement
Guerra-Peña, Kiero; Steinley, Douglas – Educational and Psychological Measurement, 2016
Growth mixture modeling is generally used for two purposes: (1) to identify mixtures of normal subgroups and (2) to approximate oddly shaped distributions by a mixture of normal components. Often in applied research this methodology is applied to both of these situations indistinctly: using the same fit statistics and likelihood ratio tests. This…
Descriptors: Growth Models, Bayesian Statistics, Sampling, Statistical Inference