Sarah D. Newton

Associate Director of RMME Online Programs

Postdoctoral Research Associate

Educational Psychology

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Current Positions:

Associate Director of Online Programs – Research Methods, Measurement, & Evaluation
Postdoctoral Research Associate – Educational Psychology
Instructor – Research Methods, Measurement, & Evaluation

 

Education:

2020 Ph.D. in Educational Psychology – Research Methods, Measurement, and Evaluation, University of Connecticut, Storrs, CT. Dissertation: “Multilevel Model Selection and Effective Sample Size—In Information Criteria We Trust” (UConn Library Archives & Special Collections: http://hdl.handle.net/11134/20002:860651160)

2018 M.A. in Educational Psychology – Research Methods, Measurement, and Evaluation, University of Connecticut, Storrs, CT.

2011 M.S. in Criminal Justice, Central Connecticut State University [CCSU], New Britain, CT. Thesis: “Examination of the psychometric properties of, and relationship between, the Belief Scale and the Criminogenic Thinking Profile” (CCSU Theses and Dissertations Identifier: Thesis 2194)

2009 B.A. in Criminology with completed course requirements in Psychology, Central Connecticut State University, New Britain, CT.

 

Research Areas:

Model/data fit and model adequacy as complementary tools for multilevel model evaluation and selection; Information criteria performance in multilevel modeling contexts; Latent variable modeling; Instrument design; Reliability and validity theory; Economic Evaluation (e.g., Cost Analysis); Quantitative research methodology
ORCid: 0000-0001-7981-7256

 

Select Publications:

McCoach, D. B., Gambino, A. J. & Newton, S. D. (2023). 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. (Cambridge Handbooks in Psychology, pp. 559-582). Cambridge: Cambridge University Press. doi:10.1017/9781009010054.027

McCoach, D. B., Newton, S. D., & Gambino, A. J. (2022). Multilevel model selection: Balancing model fit and adequacy. In M. S. Khine (Ed.), Methodology for multilevel modeling in educational research: Concepts and applications (pp. 29-48). Springer Nature.

McCoach, D. B., Newton, S. D., & Gambino, A. J. (2022). Evaluation of model fit and adequacy. In A. A. O’Connell, D. B. McCoach, & B. A. Bell (Eds.), Multilevel modeling methods with introductory and advanced applications (pp. 51-94). Information Age Publishing.

Dineen, J. N., Chafouleas, S. M., Briesch, A. M., McCoach, D. B., Newton, S. D., & Cintron, D. W. (2022). Exploring social, emotional, and behavioral screening approaches in U.S. public school districts. American Educational Research Journal, 59(1), 146-179. https://doi.org/10.3102/00028312211000043

Hamilton, R., Long, D., McCoach, D. B., Hemmler, V., Siegle, D., Newton, S. D., Gubbins, E. J., & Callahan, C. M. (2020). Proficiency and giftedness: The role of language comprehension if gifted identification and achievement. Journal for the Education of the Gifted. Advanced online publication. https://doi.org/10.1177/0162353220955225

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(5), 594-627. https://doi.org/10.3102/1076998618776348

Lawless, K. A., Brown, S. W., Rhoads, C., Lynn, L., Newton, S. D., & the GlobalEd2 Research Team. (2018). Promoting students’ science literacy skills through a simulation of international negotiations: The GlobalEd 2 project. Computers in Human Behavior, 78, 389-396. http://dx.doi.org/10.1016/j.chb.2017.08.027

McCoach, D. B., & Newton, S. D. (2017). Confirmatory factor analysis. In D. Wyse, N. Selwyn, E, Smith, & L. E. Suter (Eds.), The BERA/SAGE handbook of educational research (Vol. 2) (pp. 851-872). London: Sage Publications.

Brown, S. W., Lawless, K. A., Rhoads, C., Newton, S. D., & Lynn, L. (2016). Increasing students’ science writing skills through a PBL simulation. In D. Sampson, J. M. Spector, D. Ifenthaler & P. Isaias (Eds.), Proceedings of the 13th IADIS International Conference on Cognition and Exploratory Learning in Digital Age (CELDA) (pp. 86-94). Mannheim, Germany: International Association for Development of the Information Society. Selected as 2016 CELDA Best Paper.

McCoach, 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, 27(1), 61-81. https://doi.org/10.1080/13598139.2015.1103209