Youngsuk Suh
Biographic Data
| ID | 8399767 |
|---|---|
| NAME | Youngsuk Suh |
| GIVEN NAMES | Youngsuk |
| FAMILY NAME | Suh |
| SIGNATURE | SUH Y |
| AFFILIATIONS | Rutgers, the State University of New Jersey |
| ORCID | 0000-0001-7197-6383 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Sample Size Requirements for Simple and Complex Mediation Models
Mediation models have been widely used in many disciplines to better understand the underlying processes between independent and dependent variables. Despite their popularity and importance, the appropriate sample sizes for estimating those models are not well known. Although several approaches (such as Monte Carlo methods) exist, applied researchers tend to use insufficient sample sizes to estimate their models of interest, which might result in…
Multidimensional Extension of Multiple Indicators Multiple Causes Models to Detect DIF
A number of studies have found multiple indicators multiple causes (MIMIC) models to be an effective tool in detecting uniform differential item functioning (DIF) for individual items and item bundles. A recently developed MIMIC-interaction model is capable of detecting both uniform and nonuniform DIF in the unidimensional item response theory (IRT) framework. The goal of the current study is to extend the MIMIC-interaction model for detecting DI…
Single and Multiple Ability Estimation in the SEM Framework: A Noninformative Bayesian Estimation Approach
Latent variable models with many categorical items and multiple latent constructs result in many dimensions of numerical integration, and the traditional frequentist estimation approach, such as maximum likelihood (ML), tends to fail due to model complexity. In such cases, Bayesian estimation with diffuse priors can be used as a viable alternative to ML estimation. The present study compares the performance of Bayesian estimation to ML estimation…
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Single and Multiple Ability Estimation in the SEM Framework: A Noninformative Bayesian Estimation Approach
Latent variable models with many categorical items and multiple latent constructs result in many dimensions of numerical integration, and the traditional frequentist estimation approach, such as maximum likelihood (ML), tends to fail due to model complexity. In such cases, Bayesian estimation with diffuse priors can be used as a viable alternative to ML estimation. The present study compares the performance of Bayesian estimation to ML estimation…
Multidimensional Extension of Multiple Indicators Multiple Causes Models to Detect DIF
A number of studies have found multiple indicators multiple causes (MIMIC) models to be an effective tool in detecting uniform differential item functioning (DIF) for individual items and item bundles. A recently developed MIMIC-interaction model is capable of detecting both uniform and nonuniform DIF in the unidimensional item response theory (IRT) framework. The goal of the current study is to extend the MIMIC-interaction model for detecting DI…
Sample Size Requirements for Simple and Complex Mediation Models
Mediation models have been widely used in many disciplines to better understand the underlying processes between independent and dependent variables. Despite their popularity and importance, the appropriate sample sizes for estimating those models are not well known. Although several approaches (such as Monte Carlo methods) exist, applied researchers tend to use insufficient sample sizes to estimate their models of interest, which might result in…
Advanced Statistical Modeling Techniques (2 works) · Econometrics (2 works) · Mathematics (2 works) · Psychometric Methodologies and Testing (2 works) · Statistics (2 works) · Aeronautics (1 works) · Artificial Intelligence (1 works) · Artificial Intelligence (1 works) · Bayes estimator (1 works) · Bayes factor (1 works)