Jennifer Koran
Biographic Data
| ID | 1713479 |
|---|---|
| NAME | Jennifer Koran |
| GIVEN NAMES | Jennifer |
| FAMILY NAME | Koran |
| SIGNATURE | KORAN J |
| AFFILIATIONS | Southern Illinois University Carbondale |
| ORCID | 0000-0003-2841-4662 |
| VERIFIED | Yes |
| TOTAL WORKS | 10 |
| TOTAL CITATIONS | 4 |
| WORKS AS AUTHOR | 10 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2015 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 2 |
Accounting for Nuisance Trends Using Gaussian Processes in Dynamic Structural Equation Modeling
In modeling intensive longitudinal data with the dynamic structural equation modeling framework, this demonstration analyzes the impact of Gaussian process priors in the presence or absence of a significant trend component on the parameter estimates obtained through Bayesian analysis. The results show that even when not the focus of a research study, failing to account for the presence of trend may severely impact statistical inference and Gaussi…
Modernization of social work education in Egypt
There have been moves to examine social work education and assess its ability to respond to current and new problems around the world. This study tests a model of factors that challenge the opportunities to upgrade and modernize social work education in Egypt. A total of 226 social work educators have participated in the study by responding to an online instrument of the study model of 38 items related to seven variables. The findings of the stud…
Uncertainty in Education
Uncertainty in education, both general and special, has long troubled educational researchers, reformers, and practitioners. Responding to students with special (atypical) educational needs is an example of decisions that are prone to error. Although some efforts to reduce uncertainty in education are reasonable and helpful, efforts to eliminate uncertainty completely are not only certain to fail but sometimes make matters worse. Changing the str…
Collaboration in the Co-teacher dyad in inclusive classrooms
Indicators per Factor in Confirmatory Factor Analysis
Although some research in confirmatory factor analysis has suggested that more indicators per factor are generally better, studies have also documented that sample size requirements increase as model size increases. The present study used Monte Carlo simulation to investigate the effect of indicators per factor on sample size requirements. Results demonstrated a nonlinear association between the number of indicators per factor and the minimum req…
Evaluating the factor structure of the Multidimensional Psychological Flexibility Inventory
Deletion statistic accuracy in confirmatory factor models
Social science researchers now routinely use confirmatory factor models in scale development and validation studies. Methodologists have known for some time that the results of fitting a confirmatory factor model can be unduly influenced by one or a few cases in the data. However, there has been little development and use of case diagnostics for identifying influential cases with confirmatory factor models. A few case deletion statistics have bee…
Preliminary Proactive Sample Size Determination for Confirmatory Factor Analysis Models
Proactive preliminary minimum sample size determination can be useful for the early planning stages of a latent variable modeling study to set a realistic scope, long before the model and population are finalized. This study examined existing methods and proposed a new method for proactive preliminary minimum sample size determination
Relationships Among Classical Test Theory and Item Response Theory Frameworks via Factor Analytic Models
There are well-defined theoretical differences between the classical test theory (CTT) and item response theory (IRT) frameworks. It is understood that in the CTT framework, person and item statistics are test- and sample-dependent. This is not the perception with IRT. For this reason, the IRT framework is considered to be theoretically superior to the CTT framework for the purpose of estimating person and item parameters. In previous simulation …
Simulating Univariate and Multivariate Nonnormal Distributions through the Method of Percentiles
This article derives a standard normal-based power method polynomial transformation for Monte Carlo simulation studies, approximating distributions, and fitting distributions to data based on the method of percentiles. The proposed method is used primarily when (1) conventional (or L) moment-based estimators such as skew (or L-skew) and kurtosis (or L -kurtosis) are unknown or (2) data are unavailable but percentiles are known (e.g., standardized…
Collaboration in the Co-teacher dyad in inclusive classrooms
Preliminary Proactive Sample Size Determination for Confirmatory Factor Analysis Models
Proactive preliminary minimum sample size determination can be useful for the early planning stages of a latent variable modeling study to set a realistic scope, long before the model and population are finalized. This study examined existing methods and proposed a new method for proactive preliminary minimum sample size determination
Relationships Among Classical Test Theory and Item Response Theory Frameworks via Factor Analytic Models
There are well-defined theoretical differences between the classical test theory (CTT) and item response theory (IRT) frameworks. It is understood that in the CTT framework, person and item statistics are test- and sample-dependent. This is not the perception with IRT. For this reason, the IRT framework is considered to be theoretically superior to the CTT framework for the purpose of estimating person and item parameters. In previous simulation …
Simulating Univariate and Multivariate Nonnormal Distributions through the Method of Percentiles
This article derives a standard normal-based power method polynomial transformation for Monte Carlo simulation studies, approximating distributions, and fitting distributions to data based on the method of percentiles. The proposed method is used primarily when (1) conventional (or L) moment-based estimators such as skew (or L-skew) and kurtosis (or L -kurtosis) are unknown or (2) data are unavailable but percentiles are known (e.g., standardized…
Preliminary Proactive Sample Size Determination for Confirmatory Factor Analysis Models
Proactive preliminary minimum sample size determination can be useful for the early planning stages of a latent variable modeling study to set a realistic scope, long before the model and population are finalized. This study examined existing methods and proposed a new method for proactive preliminary minimum sample size determination
Indicators per Factor in Confirmatory Factor Analysis
Although some research in confirmatory factor analysis has suggested that more indicators per factor are generally better, studies have also documented that sample size requirements increase as model size increases. The present study used Monte Carlo simulation to investigate the effect of indicators per factor on sample size requirements. Results demonstrated a nonlinear association between the number of indicators per factor and the minimum req…
Evaluating the factor structure of the Multidimensional Psychological Flexibility Inventory
Deletion statistic accuracy in confirmatory factor models
Social science researchers now routinely use confirmatory factor models in scale development and validation studies. Methodologists have known for some time that the results of fitting a confirmatory factor model can be unduly influenced by one or a few cases in the data. However, there has been little development and use of case diagnostics for identifying influential cases with confirmatory factor models. A few case deletion statistics have bee…
Collaboration in the Co-teacher dyad in inclusive classrooms
Uncertainty in Education
Uncertainty in education, both general and special, has long troubled educational researchers, reformers, and practitioners. Responding to students with special (atypical) educational needs is an example of decisions that are prone to error. Although some efforts to reduce uncertainty in education are reasonable and helpful, efforts to eliminate uncertainty completely are not only certain to fail but sometimes make matters worse. Changing the str…
Modernization of social work education in Egypt
There have been moves to examine social work education and assess its ability to respond to current and new problems around the world. This study tests a model of factors that challenge the opportunities to upgrade and modernize social work education in Egypt. A total of 226 social work educators have participated in the study by responding to an online instrument of the study model of 38 items related to seven variables. The findings of the stud…
Accounting for Nuisance Trends Using Gaussian Processes in Dynamic Structural Equation Modeling
In modeling intensive longitudinal data with the dynamic structural equation modeling framework, this demonstration analyzes the impact of Gaussian process priors in the presence or absence of a significant trend component on the parameter estimates obtained through Bayesian analysis. The results show that even when not the focus of a research study, failing to account for the presence of trend may severely impact statistical inference and Gaussi…
Computer Science (6 works) · Mathematics (6 works) · Statistics (6 works) · Structural equation modeling (6 works) · Confirmatory factor analysis (5 works) · Psychology (5 works) · Advanced Statistical Modeling Techniques (4 works) · Econometrics (3 works) · Advanced Statistical Methods and Models (2 works) · Law (2 works)