D. Betsy McCoach

Professor, Educational Psychology

Expertise: educational measurement, latent variable modeling, multilevel modeling, instrument design, quantitative research methods, longitudinal modeling, gifted education

Educational Psychology

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Professor, Research Methods, Measurement, and Evaluation

Areas of Expertise: Educational and Psychological Measurement, Instrument Design, Latent Variable Modeling, Multilevel Modeling, Longitudinal Analysis, Quantitative Research Methodology, Gifted Education, Open Science Practices, Underachievement

Google Scholar Page

Twitter: @BetsyMcCoach

Biography:

Dr. D. Betsy McCoach is a professor of Research Methods, Measurement, and Evaluation and a faculty member in the M.S. in Data Science program at the University of Connecticut. She has extensive experience in educational measurement, latent variable and structural equation modeling, longitudinal data analysis, hierarchical linear modeling, instrument design, and factor analysis. Her substantive areas of research interest include gifted education and underachievement. Betsy has published over 100 peer reviewed journal articles, book chapters, and books, including Introduction to Modern Modeling Methods (2022) with Dakota Cintron, Multilevel Modeling Methods with Introductory and Advanced Applications (2022), with Ann O’Connell and Bethany Bell, Multilevel Modeling of Educational Data with Ann O’Connell and Instrument Development in the Affective Domain (3rd edition), co-authored with Robert K. Gable. Betsy served as the founding co-editor for the Journal of Advanced Academics and co-editor of Gifted Child Quarterly. Betsy is the founder and conference chair of the Modern Modeling Methods conference, held at UCONN. Betsy has served as a Co-Principal Investigator and research methodologist on several federally funded research grants, including the National Center for Research on Gifted Education, Evaluating the Impact of Integrated Behavior and Reading Multi-Tiered Systems of Support in Elementary Schools, and Project NEEDs2, all funded by IES, and Science of Learning and Art of Communication (SLAC), funded by NSF. Betsy is past chair of several AERA SIGs, including the Structural Equation Modeling SIG, Multilevel Modeling SIG, Educational Statisticians SIG, and Research on Giftedness, Creativity, and Talent Development SIG. Betsy is a fellow of the American Psychological Association, Division 5, and winner of the 2022 Distinguished Scholar award from the National Association of Gifted Children (NAGC). She currently sits on the Board of Directors for NAGC.

Funded Research (Selected):

Co-Principal Investigator, National Center for Research on Gifted Education

Co-Principal Investigator, National Exploration of Emotional/Behavioral Detection in School Screening (NEEDs²)

Co-Principal Investigator, Science of learning, from neurobiology to real-world application: a problem-based approach. Funding Source: NSF ($3 million) PI: James Magnuson.

Project Director/Principal Investigator. Project PAPER: Preparing Academicians in Psychometrics and Educational Research. (2012-2015). U. S. Department of Education, $399,000.

Selected Recent Publications/Presentations:

Books

McCoach, D. B. & Cintron, D. W.* (2022).  Introduction to Modern Modeling Methods. London: SAGE.

O’Connell, A.A., McCoach, D.B. , & Bell, B. A. (2022).  Multilevel Modeling Methods with Introductory and Advanced Applications. (Eds.) Charlotte, NC: Information Age Publishing.

McCoach, D. B., Gable, R. K., & Madura, J. (2013). Instrument Design in the Affective Domain. (Third Edition). New York: Springer.

Peters, S., McBee, M., Matthews, M., & McCoach, D. B. (2013). Beyond gifted education: Designing and implementing advanced academic programs. Waco, TX: Prufrock Press.

O’Connell, A.A. & McCoach, D.B. (2008).  Multilevel modeling of educational data. (Eds.) Charlotte, NC: Information Age Publishing.

Selected Journal Articles

McCoach, D. B., Peters, S., Gambino, A. J., Long, D., & Siegle, D. (in press). Who are we measuring? Teacher effects in gifted and talented teacher rating scales. Exceptional Children.

Cintron, D. W.*, Loken, E., & McCoach, D. B. (2023). A cautionary note about having the right mixture model but classifying the wrong people. Multivariate Behavioral Research, 58 (4), 675-686. https://doi.org/10.1080/00273171.2022.2082913

 

Coyne, M. D., McCoach, D. B., Ware, S., Loftus-Rattan, S., Baker, D., Santoro, L., & Oldham, A. (2022). Supporting vocabulary development within a multi-tiered system of support: Evaluating the efficacy of supplementary kindergarten vocabulary intervention. Journal of Educational Psychology, 114(6), 1225-1241. http://dx.doi.org/10.1037/edu0000724

Long, D., McCoach, D. B., Siegle, D., Callahan, C. M., & Gubbins, E. J. (2023). Inequality at the Starting Line: Under-Representation in Gifted Identification and Disparities in Early Achievement.  AERA Open, 9. https://doi.org/10.1177/23328584231171

Dineen, J., Chafouleas, S., Briesch, A. M., McCoach, D. B., Newton, S. D., & Cintron, D. W. (2022). Exploring Approaches to Identifying and Supporting Students’ Social, Emotional, and Behavioral Needs in U.S. Public School Districts.  American Educational Research Journal, 59(1), 146-179. https://doi.org/10.3102/00028312211000043

McCoach, D. B. (2022). Achieving Equity Within Public Education. Gifted Child Quarterly.

Yu, H.*, Lupas, K. K., Chafouleas, S. M., McCoach, D. B., Fabiano, G. A., Riley-Tillman, T. C., Welsh, M. E., & Volk, D. T. (2022). Timing and frequency of screening in schools: A latent variable analysis of stability over time. Psychological Assessment, 34 (10), 952-965. DOI: 10.1037/pas0001157

Gubbins, E. J., Siegle, D., Cross, K., McCoach, D. B., Dulong Langley, S., Callahan, C., Brodersen, A., & Caughey, M. (2021). Identifying and Serving Gifted and Talented Students: Are Identification and Services Connected? Gifted Child Quarterly, 65(2), 115-131.

McCoach, D. B., Siegle, D., & Rubenstein, L. (2020). Pay attention to inattention: Exploring ADHD symptoms in a sample of underachieving gifted students. Gifted Child Quarterly, 64(2) 100–116. https://doi.org/10.1177/0016986219901320

Coyne, M. D., McCoach, D. B., Ware, S., Austin, C. R., Loftus-Rattan, S. M., & Baker, D. L., (2019). Racing Against the Vocabulary Gap: Matthew Effects in Early Vocabulary Instruction and Intervention.  Exceptional Children, 85, 163-179.

McCoach, D. B., Rifenbark, G.*, Newton, S. D.*, Li, X.*, Kooken, J.*, Yomtov, D.*, Gambino, A.*, & Bellara, A.  (2018). Does the package matter? A Comparison of Five Common Multilevel Modeling Software Packages. Journal of Educational and Behavioral Statistics, 43, 594-627.

Hamilton. R., McCoach, D. B., Tutwiler, M. S., Siegle, D., Callahan, C., Gubbins, E. J., & Broderson, A. (2018). Disentangling the roles of institutional and individual poverty in the identification of gifted students. Gifted Child Quarterly, 62, 6-24. http://journals.sagepub.com/doi/pdf/10.1177/0016986217738053

Kooken, J*., McCoach, D. B., & Chafouleas, S. M. (2018). The Impact and Interpretation of Residual Non-invariance in Growth Mixture Modeling. Journal of Experimental Education. https://doi.org/10.1080/10705511.2017.1374187

Yu, H. H.*, McCoach, D. B., Gottfried, A. W., & Gottfried, A. E. (2018). Stability of Intelligence from Infancy through Adolescence: An Autoregressive Latent Variable Model.  Intelligence, 69, 8-15.

Flake, J.* & McCoach, D. B. (2017). An Investigation of the Alignment Method with polytomous indicators under conditions of partial measurement invariance.  Structural Equation Modeling. Online First: http://dx.doi.org/10.1080/10705511.2017.1374187

McCoach, D. B., Yu, H. H., Gottfried, A. W., Gottfried, A. E. (2017). Developing Talents: A Longitudinal Examination of Intellectual Ability and Academic Achievement. High Ability Studies. http://dx.doi.org/10.1080/13598139.2017.1298996

McCoach, D. B., Newton, S. D., Siegle, D., Baslanti, U, & Picho, K. (2016).  Is Having Low Motivation the Same as Not Having High Motivation? Comparing the CSAS-R and the SAAS-R.  High Ability Studies. DOI: 10.1080/13598139.2015.1103209

McCoach, D. B. & Kenny, D. A. (2014). A Few Thoughts on the Similarities and the Differences Between Causal or Reflective Indicators of Latent Variables. Measurement: Interdisciplinary Perspectives, 12, 151-154. https://doi.org/10.1080/15366367.2014.981067

McCoach, D. B., Gubbins, E. J., Foreman, J., Rubenstein, L., & Rambo, K., (2014). Evaluating the Efficacy of Using Pre-differentiated and Enriched Mathematics Curricula for Grade 3 Students. Gifted Child Quarterly. https://doi.org/10.1177/0016986214547631

Kenny, D. A., *Kaniskan, B., & McCoach, D. B. (2014). How small is too small? The performance of RMSEA in models with small df. Sociological Research Methods. https://doi.org/10.1177/0049124114543236

*Rambo, K. & McCoach, D. B. (2014). Using summer growth patterns to assess the impact of schools on high achieving and gifted students’ reading skills. Journal of Educational Research. DOI: 10.1080/00220671.2013.850398

McCoach, D. B., Rambo, K., & Welsh, M. (2013).  Assessing the growth of gifted students. Gifted Child Quarterly, 57, 56-67. https://doi.org/10.1177/0016986212463873

*Adelson, J. L., McCoach, D. B., & Gavin, M. K. (2012). Examining the effects of gifted programming in mathematics and reading using the ECLS-K. Gifted Child Quarterly, 56, 25-39. https://doi.org/10.1177/0016986211431487 

*Black, A. C., Harel, O., & McCoach, D. B. (2011). Missing data techniques for multilevel data: implications of model misspecification. Journal of Applied Statistics, DOI: 10.1080/02664763.2010.529882

McCoach, D. B., & Colbert, R. D. (2010). Factors underlying the Collective Teacher Efficacy Scale and their mediating role in the effect of socio-economic status on academic achievement at the school level. Measurement and Evaluation in Counseling and Development, 43, 31-47. https://doi.org/10.1177/0748175610362368

McCoach, D. B., Goldstein, J., Behuniak, P., Reis, S. M., Black, A. C., Rambo, K., & Sullivan, E. (2010). Examining the unexpected: Outlier analyses of factors affecting student achievement. Journal of Advanced Academics, 21, 426-268.

McCoach, D. B. & Kaniskan, B. (2010). Using time varying covariates in multilevel growth models. Frontiers in Quantitative Psychology and Measurement, 1:17. DOI: 10.3389/fpsyg.2010.00017

McCoach, D. B. (2010). Dealing with dependence (Part II): A gentle introduction to Hierarchical Linear Modeling. Gifted Child Quarterly, 54, 252-256.  https://doi.org/10.1177/0016986210373475

McCoach, D. B. & Adelson, J. (2010). Dealing with dependence (Part I): Understanding the effects of Clustered Data. Gifted Child Quarterly, 54, 152-155. DOI: 10.1177/0016986210363076

Kenny, D. A. & McCoach, D. B. (2003).  Effect of the number of variables on measures of fit in Structural Equation Modeling. Structural Equation Modeling, 10, 333-351. DOI: http://dx.doi.org/10.1207/S15328007SEM1003_1

McCoach, D. B., & Siegle, D. (2003).  Factors that differentiate underachieving gifted students from high achieving gifted students.  Gifted Child Quarterly, 47, 144-154. DOI: http://dx.doi.org/10.1177/001698620304700205

McCoach, D. B. & Siegle, D. (2003).  The School Attitude Assessment Survey – Revised: A new instrument to identify academically able students who underachieve.  Educational and Psychological Measurement, 63, 414-429. DOI: http://dx.doi.org/10.1177/0013164403063003005

Selected Book Chapters 

McCoach, D. B., Bell, B. A., & Bellara, A. P.   (2022). Individual Growth Curve Models for Longitudinal Data. In A.A. O’Connell, D. B. McCoach, & B. A. Bell (Eds.) Multilevel Modeling Methods with Introductory and Advanced Applications. Information Age Press.

McCoach, D. B., Gambino, A. & Newton, S. D. (2022). Multilevel Modeling.  In A. L. Nichols & J. E. Edlund (Eds.) Cambridge Handbook of Research Methods and Statistics for the Social and Behavioral Sciences: Volume 1 Building a Program of Research.

McCoach, D. B., Newton, S. D., & Gambino, A. (2022). Evaluating the fit and adequacy of multilevel models. In A.A. O’Connell, D. B. McCoach, & B. A. Bell (Eds.) Multilevel Modeling Methods with Introductory and Advanced Applications. Information Age Press.

McCoach, D. B., Newton, S. D., & Gambino, A. (2022). Multilevel Model Selection: Balancing Model Fit and Adequacy. In Khine (Ed). Methodology for Multilevel Modeling in Educational Research: Concepts and Applications. (pp. 29-48). Springer.

O’Connell, A. A., McCoach, D. B., & Bell, B. A. (2022). Introduction to Multilevel Modeling Methods: Pedagogy and Context. In A.A. O’Connell, D. B. McCoach, & B. A. Bell (Eds.) Multilevel Modeling Methods with Introductory and Advanced Applications. Information Age Press.

McCoach, D. B., Dineen, J. N., Chafouleas, S. M., & Briesh, A. (2020). Reproducibility in the era of Big Data: Lessons for developing robust data management and data analysis procedures. In C. A. Hill, P. P. Biemer, T. D. Buskirk, L. Japec, A. Kirchner, S. Kolenikov, & L. E. Lyberg (Eds.) Big Data Meets Survey Science: A Collection of Innovative Methods. John Wiley and Sons.

McCoach, D. B. (2018). Multilevel modeling. In G. R. Hancock & R. O. Mueller (Eds.) The reviewer’s guide to quantitative methods in the social sciences (Revised). New York: Routledge.

McCoach, D. B., & Rambo, K. (2018). Issues in the analysis of change.  In C. Secolsky (Ed.) Handbook of measurement, assessment, and evaluation in higher education (Second edition).

McCoach, D. B. & Flake, J. (2017). Motivation of gifted students.  In APA Handbook of Gifted Education and Talent Development.  Washington, D.C.: APA.

McCoach, D. B. & Newton, S. D. (2017).  Confirmatory Factor Analysis. In BERA-SAGE Handbook of Research Methods in Education.

O’Connell, A. A., Yeomans‐Maldonado, G., & McCoach, D. B. (2016.)  Residual Diagnostics and Model Assessment in a Multilevel Framework: Recommendations toward Best Practice. In J. Harring, L. Stapleton, & T. Beretvas (Eds.) Advances in Multilevel Modeling for Educational Research.  Charlotte, NC: Information Age.

McCoach, D. B. & Yu, H. H. (2016). Using individual growth curve models to understand reading fluency development. The Fluency Construct. New York. Springer.

Associations/Committees/Outreach:

Modern Modeling Methods Conference