Publication Date
In 2025 | 0 |
Since 2024 | 3 |
Since 2021 (last 5 years) | 5 |
Since 2016 (last 10 years) | 9 |
Since 2006 (last 20 years) | 12 |
Descriptor
Source
Author
James Ohisei Uanhoro | 2 |
Arav, Marina | 1 |
Asparouhov, Tihomir | 1 |
Beauducel, André | 1 |
Ben Kelcey | 1 |
Canivez, Gary L. | 1 |
Cooke, Lucy | 1 |
Corlu, M. Sencer | 1 |
Cross, Jennifer Riedl | 1 |
Cross, Tracy L. | 1 |
Dombrowski, Stefan C. | 1 |
More ▼ |
Publication Type
Journal Articles | 11 |
Reports - Research | 9 |
Reports - Descriptive | 3 |
Education Level
Higher Education | 1 |
Junior High Schools | 1 |
Middle Schools | 1 |
Postsecondary Education | 1 |
Secondary Education | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
Differential Aptitude Test | 1 |
What Works Clearinghouse Rating
James Ohisei Uanhoro – Structural Equation Modeling: A Multidisciplinary Journal, 2024
We present a method for Bayesian structural equation modeling of sample correlation matrices as correlation structures. The method transforms the sample correlation matrix to an unbounded vector using the matrix logarithm function. Bayesian inference about the unbounded vector is performed assuming a multivariate-normal likelihood, with a mean…
Descriptors: Bayesian Statistics, Structural Equation Models, Correlation, Monte Carlo Methods
Edgar C. Merkle; Oludare Ariyo; Sonja D. Winter; Mauricio Garnier-Villarreal – Grantee Submission, 2023
We review common situations in Bayesian latent variable models where the prior distribution that a researcher specifies differs from the prior distribution used during estimation. These situations can arise from the positive definite requirement on correlation matrices, from sign indeterminacy of factor loadings, and from order constraints on…
Descriptors: Models, Bayesian Statistics, Correlation, Evaluation Methods
James Ohisei Uanhoro – Educational and Psychological Measurement, 2024
Accounting for model misspecification in Bayesian structural equation models is an active area of research. We present a uniquely Bayesian approach to misspecification that models the degree of misspecification as a parameter--a parameter akin to the correlation root mean squared residual. The misspecification parameter can be interpreted on its…
Descriptors: Bayesian Statistics, Structural Equation Models, Simulation, Statistical Inference
Beauducel, André; Hilger, Norbert – Educational and Psychological Measurement, 2022
In the context of Bayesian factor analysis, it is possible to compute plausible values, which might be used as covariates or predictors or to provide individual scores for the Bayesian latent variables. Previous simulation studies ascertained the validity of mean plausible values by the mean squared difference of the mean plausible values and the…
Descriptors: Bayesian Statistics, Factor Analysis, Prediction, Simulation
Liang, Xinya – Educational and Psychological Measurement, 2020
Bayesian structural equation modeling (BSEM) is a flexible tool for the exploration and estimation of sparse factor loading structures; that is, most cross-loading entries are zero and only a few important cross-loadings are nonzero. The current investigation was focused on the BSEM with small-variance normal distribution priors (BSEM-N) for both…
Descriptors: Factor Structure, Bayesian Statistics, Structural Equation Models, Goodness of Fit
Fangxing Bai; Ben Kelcey – Society for Research on Educational Effectiveness, 2024
Purpose and Background: Despite the flexibility of multilevel structural equation modeling (MLSEM), a practical limitation many researchers encounter is how to effectively estimate model parameters with typical sample sizes when there are many levels of (potentially disparate) nesting. We develop a method-of-moment corrected maximum likelihood…
Descriptors: Maximum Likelihood Statistics, Structural Equation Models, Sample Size, Faculty Development
Dombrowski, Stefan C.; Golay, Philippe; McGill, Ryan J.; Canivez, Gary L. – Psychology in the Schools, 2018
Bayesian structural equation modeling (BSEM) was used to investigate the latent structure of the Differential Ability Scales-Second Edition core battery using the standardization sample normative data for ages 7-17. Results revealed plausibility of a three-factor model, consistent with publisher theory, expressed as either a higher-order (HO) or a…
Descriptors: Structural Equation Models, Bayesian Statistics, Factor Analysis, Aptitude Tests
Smith, Andrea D.; Herle, Moritz; Fildes, Alison; Cooke, Lucy; Steinsbekk, Silje; Llewellyn, Clare H. – Journal of Child Psychology and Psychiatry, 2017
Background: "Food fussiness" (FF) is the tendency to be highly selective about which foods one is willing to eat, and emerges in early childhood; "food neophobia" (FN) is a closely related characteristic but specifically refers to rejection of unfamiliar food. These behaviors are associated, but the extent to which their…
Descriptors: Food, Fear, Genetics, Environmental Influences
Mammadov, Sakhavat; Ward, Thomas J.; Cross, Jennifer Riedl; Cross, Tracy L. – Roeper Review, 2016
To date, in gifted education and related fields various conventional factor analytic and clustering techniques have been used extensively for investigation of the underlying structure of data. Latent profile analysis is a relatively new method in the field. In this article, we provide an introduction to latent profile analysis for gifted education…
Descriptors: Statistical Analysis, Academically Gifted, Factor Analysis, Multivariate Analysis
Muthen, Bengt; Asparouhov, Tihomir – Psychological Methods, 2012
This article proposes a new approach to factor analysis and structural equation modeling using Bayesian analysis. The new approach replaces parameter specifications of exact zeros with approximate zeros based on informative, small-variance priors. It is argued that this produces an analysis that better reflects substantive theories. The proposed…
Descriptors: Factor Analysis, Cognitive Ability, Science Achievement, Structural Equation Models
Corlu, M. Sencer – International Review of Education, 2014
There are two mainstream curricula for international school students at the junior high level: the International Baccalaureate (IB) Middle Years Programme (MYP) and the Cambridge International General Certificate of Secondary Education (IGCSE). The former was developed in the mid-1990s and is currently being relaunched in a 21st-century approach.…
Descriptors: Advanced Placement Programs, Junior High School Students, International Schools, Educational Change
Hayashi, Kentaro; Arav, Marina – Educational and Psychological Measurement, 2006
In traditional factor analysis, the variance-covariance matrix or the correlation matrix has often been a form of inputting data. In contrast, in Bayesian factor analysis, the entire data set is typically required to compute the posterior estimates, such as Bayes factor loadings and Bayes unique variances. We propose a simple method for computing…
Descriptors: Bayesian Statistics, Factor Analysis, Correlation, Matrices