Sarah D. Newton

Associate Director of RMME Online Programs

Postdoctoral Research Associate

Educational Psychology


Current Positions:

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



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:

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.

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.

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.

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.

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.


Dr. Sarah D. Newton
Contact Information
Mailing Address249 Glenbrook Road, Unit 3064
Office LocationGentry 119A
Office HoursBy Appointment
CoursesEPSY5605; EPSY5601
LinkResearch Methods, Measurement, and Evaluation (RMME) programs