Insu Paek
Dados Biográficos
| ID | 8867579 |
|---|---|
| NOME | Insu Paek |
| PRENOMES | Insu |
| SOBRENOME | Paek |
| ASSINATURA | PAEK I |
| AFILIAÇÕES | Florida State University, Tallahassee, FL, USA |
| ORCID | 0000-0002-2552-9475 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 8 |
| TOTAL DE CITAÇÕES | 0 |
| OBRAS COMO AUTOR | 8 |
| OBRAS COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2011 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2023 |
| ÍNDICE H | 0 |
Investigating Confidence Intervals of Item Parameters When Some Item Parameters Take Priors in the 2PL and 3PL Models
To reduce the chance of Heywood cases or nonconvergence in estimating the 2PL or the 3PL model in the marginal maximum likelihood with the expectation-maximization (MML-EM) estimation method, priors for the item slope parameter in the 2PL model or for the pseudo-guessing parameter in the 3PL model can be used and the marginal maximum a posteriori (MMAP) and posterior standard error (PSE) are estimated. Confidence intervals (CIs) for these paramet…
A Log-Linear Modeling Approach for Differential Item Functioning Detection in Polytomously Scored Items
A log-linear model (LLM) is a well-known statistical method to examine the relationship among categorical variables. This study investigated the performance of LLM in detecting differential item functioning (DIF) for polytomously scored items via simulations where various sample sizes, ability mean differences (impact), and DIF types were manipulated. Also, the performance of LLM was compared with that of other observed score-based DIF methods, n…
Estimation of an IRT Model by Mplus for Dichotomously Scored Responses Under Different Estimation Methods
The purpose of this article is twofold. The first is to provide evaluative information on the recovery of model parameters and their standard errors for the two-parameter item response theory (IRT) model using different estimation methods by Mplus. The second is to provide easily accessible information for practitioners, instructors, and students about the relationships between IRT and item factor analysis (FA) parameterizations. Specifically, th…
Evaluating the Impact of Guessing and Its Interactions With Other Test Characteristics on Confidence Interval Procedures for Coefficient Alpha
The effect of guessing on the point estimate of coefficient alpha has been studied in the literature, but the impact of guessing and its interactions with other test characteristics on the interval estimators for coefficient alpha has not been fully investigated. This study examined the impact of guessing and its interactions with other test characteristics on four confidence interval (CI) procedures for coefficient alpha in terms of coverage rat…
Specifying Ability Growth Models Using a Multidimensional Item Response Model for Repeated Measures Categorical Ordinal Item Response Data
When categorical ordinal item response data are collected over multiple timepoints from a repeated measures design, an item response theory (IRT) modeling approach whose unit of analysis is an item response is suitable. This study proposes a few longitudinal IRT models and illustrates how a popular compensatory multidimensional IRT model can be utilized to formulate such longitudinal IRT models, which permits an investigation of ability growth at…
A Comparison of Three IRT Approaches to Examinee Ability Change Modeling in a Single-Group Anchor Test Design
Typically a longitudinal growth modeling based on item response theory (IRT) requires repeated measures data from a single group with the same test design. If operational or item exposure problems are present, the same test may not be employed to collect data for longitudinal analyses and tests at multiple time points are constructed with unique item sets, as well as a set of common items (i.e., anchor test) for a study of examinee growth. In thi…
A Comparison of Item Parameter Standard Error Estimation Procedures for Unidimensional and Multidimensional Item Response Theory Modeling
The present study was motivated by the recognition that standard errors ( SEs) of item response theory (IRT) model parameters are often of immediate interest to practitioners and that there is currently a lack of comparative research on different SE (or error variance–covariance matrix) estimation procedures. The present study investigated item parameter SEs based on three error variance–covariance matrix estimation procedures for unidimensional …
Formulating the Rasch Differential Item Functioning Model Under the Marginal Maximum Likelihood Estimation Context and Its Comparison With Mantel–Haenszel Procedure in Short Test and Small Sample Cond…
This study elaborates the Rasch differential item functioning (DIF) model formulation under the marginal maximum likelihood estimation context. Also, the Rasch DIF model performance was examined and compared with the Mantel–Haenszel (MH) procedure in small sample and short test length conditions through simulations. The theoretically known relationship of the DIF estimators between the Rasch DIF model and the MH procedure was confirmed. In genera…
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Formulating the Rasch Differential Item Functioning Model Under the Marginal Maximum Likelihood Estimation Context and Its Comparison With Mantel–Haenszel Procedure in Short Test and Small Sample Cond…
This study elaborates the Rasch differential item functioning (DIF) model formulation under the marginal maximum likelihood estimation context. Also, the Rasch DIF model performance was examined and compared with the Mantel–Haenszel (MH) procedure in small sample and short test length conditions through simulations. The theoretically known relationship of the DIF estimators between the Rasch DIF model and the MH procedure was confirmed. In genera…
A Comparison of Three IRT Approaches to Examinee Ability Change Modeling in a Single-Group Anchor Test Design
Typically a longitudinal growth modeling based on item response theory (IRT) requires repeated measures data from a single group with the same test design. If operational or item exposure problems are present, the same test may not be employed to collect data for longitudinal analyses and tests at multiple time points are constructed with unique item sets, as well as a set of common items (i.e., anchor test) for a study of examinee growth. In thi…
A Comparison of Item Parameter Standard Error Estimation Procedures for Unidimensional and Multidimensional Item Response Theory Modeling
The present study was motivated by the recognition that standard errors ( SEs) of item response theory (IRT) model parameters are often of immediate interest to practitioners and that there is currently a lack of comparative research on different SE (or error variance–covariance matrix) estimation procedures. The present study investigated item parameter SEs based on three error variance–covariance matrix estimation procedures for unidimensional …
Evaluating the Impact of Guessing and Its Interactions With Other Test Characteristics on Confidence Interval Procedures for Coefficient Alpha
The effect of guessing on the point estimate of coefficient alpha has been studied in the literature, but the impact of guessing and its interactions with other test characteristics on the interval estimators for coefficient alpha has not been fully investigated. This study examined the impact of guessing and its interactions with other test characteristics on four confidence interval (CI) procedures for coefficient alpha in terms of coverage rat…
Specifying Ability Growth Models Using a Multidimensional Item Response Model for Repeated Measures Categorical Ordinal Item Response Data
When categorical ordinal item response data are collected over multiple timepoints from a repeated measures design, an item response theory (IRT) modeling approach whose unit of analysis is an item response is suitable. This study proposes a few longitudinal IRT models and illustrates how a popular compensatory multidimensional IRT model can be utilized to formulate such longitudinal IRT models, which permits an investigation of ability growth at…
Estimation of an IRT Model by Mplus for Dichotomously Scored Responses Under Different Estimation Methods
The purpose of this article is twofold. The first is to provide evaluative information on the recovery of model parameters and their standard errors for the two-parameter item response theory (IRT) model using different estimation methods by Mplus. The second is to provide easily accessible information for practitioners, instructors, and students about the relationships between IRT and item factor analysis (FA) parameterizations. Specifically, th…
A Log-Linear Modeling Approach for Differential Item Functioning Detection in Polytomously Scored Items
A log-linear model (LLM) is a well-known statistical method to examine the relationship among categorical variables. This study investigated the performance of LLM in detecting differential item functioning (DIF) for polytomously scored items via simulations where various sample sizes, ability mean differences (impact), and DIF types were manipulated. Also, the performance of LLM was compared with that of other observed score-based DIF methods, n…
Investigating Confidence Intervals of Item Parameters When Some Item Parameters Take Priors in the 2PL and 3PL Models
To reduce the chance of Heywood cases or nonconvergence in estimating the 2PL or the 3PL model in the marginal maximum likelihood with the expectation-maximization (MML-EM) estimation method, priors for the item slope parameter in the 2PL model or for the pseudo-guessing parameter in the 3PL model can be used and the marginal maximum a posteriori (MMAP) and posterior standard error (PSE) are estimated. Confidence intervals (CIs) for these paramet…
Mathematics (8 obras) · Statistics (8 obras) · Advanced Statistical Modeling Techniques (7 obras) · Econometrics (7 obras) · Psychometric Methodologies and Testing (7 obras) · Item response theory (6 obras) · Psychometrics (6 obras) · Psychology (4 obras) · Computer Science (3 obras) · Categorical variable (2 obras)