Kari J. Hodge
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Kari J. Hodge has a total of 12 co-authors. Here are the top co-authors by number of shared publications:
- Grant B. Morgan
Baylor University, Waco, TX, USA
4 shared publications Aaron R. Baggett
1 shared publicationGrant B. Morgan
1 shared publicationJason Trumble
Baylor University, Waco, TX, USA
1 shared publication- Kevin Eugene Wells
Baylor University
1 shared publication - Lorin W. Anderson
University of South Carolina
1 shared publication
Latest Publications
- 1 January 2016
- Published by Elsevier in Computational Statistics & Data Analysis
- Vol. 93, 146-161
Latent profile analysis with nonnormal mixtures: A Monte Carlo examination of model selection using fit indices
- 1 January 2016
- Published by Elsevier in Computational Statistics & Data Analysis
- Vol. 93, 146-161
Latent profile analysis with nonnormal mixtures: A Monte Carlo examination of model selection using fit indices
- Open Access
- 3 February 2015
- Published by MDPI AG in Journal of Intelligence
- Vol. 3 (1) , 2-20
Are Fit Indices Biased in Favor of Bi-Factor Models in Cognitive Ability Research?: A Comparison of Fit in Correlated Factors, Higher-Order, and Bi-Factor Models via Monte Carlo Simulations
Bi-factor confirmatory factor models have been influential in research on cognitive abilities because they often better fit the data than correlated factors and higher-order models. They also instantiate a perspective that differs from that offered by other models. Motivated by previous work that hypothesized an inherent statistical bias of fit indices favoring the bi-factor model, we compared the fit of correlated factors, higher-order, and bi-factor models via Monte Carlo methods. When data were sampled from a true bi-factor structure, each of the approximate fit indices was more likely than not to identify the bi-factor solution as the best fitting. When samples were selected from a true multiple correlated factors structure, approximate fit indices were more likely overall to identify the correlated factors solution as the best fitting. In contrast, when samples were generated from a true higher-order structure, approximate fit indices tended to identify the bi-factor solution as best fitting. There was extensive overlap of fit values across the models regardless of true structure. Although one model may fit a given dataset best relative to the other models, each of the models tended to fit the data well in absolute terms. Given this variability, models must also be judged on substantive and conceptual grounds.
- 3 February 2015
- Published by MDPI AG in Journal of Intelligence
- Vol. 3 (1) , 2-20
Open AccessAre Fit Indices Biased in Favor of Bi-Factor Models in Cognitive Ability Research?: A Comparison of Fit in Correlated Factors, Higher-Order, and Bi-Factor Models via Monte Carlo Simulations
Bi-factor confirmatory factor models have been influential in research on cognitive abilities because they often better fit the data than correlated factors and higher-order models. They also instantiate a perspective that differs from that offered by other models. Motivated by previous work that hypothesized an inherent statistical bias of fit indices favoring the bi-factor model, we compared the fit of correlated factors, higher-order, and bi-factor models via Monte Carlo methods. When data were sampled from a true bi-factor structure, each of the approximate fit indices was more likely than not to identify the bi-factor solution as the best fitting. When samples were selected from a true multiple correlated factors structure, approximate fit indices were more likely overall to identify the correlated factors solution as the best fitting. In contrast, when samples were generated from a true higher-order structure, approximate fit indices tended to identify the bi-factor solution as best fitting. There was extensive overlap of fit values across the models regardless of true structure. Although one model may fit a given dataset best relative to the other models, each of the models tended to fit the data well in absolute terms. Given this variability, models must also be judged on substantive and conceptual grounds.
- Open Access
- 6 October 2014
- Published by Mary Lou Fulton College for Teaching and Learning Innovation in Education Policy Analysis Archives
- Vol. 22, 95
The Stability of Teacher Performance and Effectiveness: Implications for Policies Concerning Teacher Evaluation
The Stability of Teacher Performance and Effectiveness: Implications for Policies Concerning Teacher Evaluation
- 6 October 2014
- Published by Mary Lou Fulton College for Teaching and Learning Innovation in Education Policy Analysis Archives
- Vol. 22, 95
Open AccessThe Stability of Teacher Performance and Effectiveness: Implications for Policies Concerning Teacher Evaluation
The Stability of Teacher Performance and Effectiveness: Implications for Policies Concerning Teacher Evaluation
- 3 July 2014
- Published by Taylor & Francis in Language Assessment Quarterly
- Vol. 11 (3) , 304-324
Interrater Reliability Estimators Commonly Used in Scoring Language Assessments: A Monte Carlo Investigation of Estimator Accuracy
- 3 July 2014
- Published by Taylor & Francis in Language Assessment Quarterly
- Vol. 11 (3) , 304-324
Interrater Reliability Estimators Commonly Used in Scoring Language Assessments: A Monte Carlo Investigation of Estimator Accuracy
- 23 November 2013
- Published by Springer Nature in Quality & Quantity
- Vol. 49 (1) , 1-20
Major differences: modeling profiles of community college persisters in career clusters
- 23 November 2013
- Published by Springer Nature in Quality & Quantity
- Vol. 49 (1) , 1-20
Major differences: modeling profiles of community college persisters in career clusters
- 1 April 2013
- Published by IGI Global Scientific Publishing in International Journal of Web-Based Learning and Teaching Technologies
- Vol. 8 (2) , 77-105
A Cross-Country Comparison of Virtual Discussion Board Use in United States and Costa Rican Education Settings
The purpose of the current study was to compare the use of virtual discussion boards in various educational settings in the United States and Costa Rica. Participants included professors of education, in-service and pre-service teachers in the United States and Costa Rica where a survey was used that included demographic, knowledge, attitude, and behavioral questions regarding the use of virtual discussion boards. Results indicated that sixty-two percent of the participants used discussion boards in an educational setting. Instructors reported creating discussion board prompts that were constructivist in nature, and responses were frequently assessed for reflection, application, or collaboration. Findings show implications for educators in Costa Rica the United States due to the extensive rural landscape that perpetuates a need for alternative forms of communication and distance learning as well as to provide a comparison to how this technology is used in United States educational settings.
- 1 April 2013
- Published by IGI Global Scientific Publishing in International Journal of Web-Based Learning and Teaching Technologies
- Vol. 8 (2) , 77-105
A Cross-Country Comparison of Virtual Discussion Board Use in United States and Costa Rican Education Settings
The purpose of the current study was to compare the use of virtual discussion boards in various educational settings in the United States and Costa Rica. Participants included professors of education, in-service and pre-service teachers in the United States and Costa Rica where a survey was used that included demographic, knowledge, attitude, and behavioral questions regarding the use of virtual discussion boards. Results indicated that sixty-two percent of the participants used discussion boards in an educational setting. Instructors reported creating discussion board prompts that were constructivist in nature, and responses were frequently assessed for reflection, application, or collaboration. Findings show implications for educators in Costa Rica the United States due to the extensive rural landscape that perpetuates a need for alternative forms of communication and distance learning as well as to provide a comparison to how this technology is used in United States educational settings.