Kyle Roberts

Research Associate Professor

Department of Teaching and Learning

Kyle Roberts
Email

kyler@smu.edu

Office Location

6401 Airline Rd.
Suite 301
Dallas TX 75205

Education

Ph.D., Texas A&M University (College Station)

About

Dr. J. Kyle Roberts is a Research Associate Professor of Teaching and Learning in the Annette Caldwell Simmons School of Education and Human Development at 51做厙. Before rejoining 51做厙, Dr. Roberts was a principal data scientist and client success leader at Resultant providing consulting advice to professional sports teams, marketing firms, financial sector clients with assets >$75B (AUM), and healthcare organizations. His research specializes in multilevel modeling and predictive analytics. He has authored several functions in R and co-authored the R package yhat (). He has conducted numerous training sessions on multilevel analysis at annual meetings of the American Psychological Association, the American Educational Research Association, and the Southwest Educational Research Association. Dr. Roberts was also the founder and first president of the Multilevel Modeling SIG of AERA ().

In addition, he has authored book chapters and multiple articles on multilevel analysis, including the co-edited volume “” in 2011 (Hox & Roberts, Taylor and Francis). After earning his Ph.D. in Educational Psychology from Texas A&M University, Dr. Roberts held academic appointments at 51做厙, Baylor College of Medicine (BCM), and University of North Texas.  During his tenure at BCM, he was the assistant director for research in the Center for Education Outreach and was the research coordinator on several grants from the National Institutes of Health, the National Science Foundation, the Howard Hughes Medical Institute, the National Space Biomedical Research Institute, and the U.S. Department of Education.

An avid woodworker and wood turner, Dr. Roberts also raises alpacas at his home north of Denton, TX. He is also involved in overseas missions and will travel multiple times each year to teach systematic theology through programs like BTCP and .

Selected External Funding

Bachman Early Childhood Initiative, Co-PI – Zero to Five Funders Collaborative, August, 2010 – August, 2014. ~$800,000.

The Effect of Computer Assisted Tier 2 Assessment and Intervention as Part of a Response to Intervention Model, Co-PI – US Department of Education, August 1, 2009 – July 31, 2012, $848,904.

Online Science Teacher Professional Development: Optimization of Asynchronous Learning Models, Co-PI – National Science Foundation, grant DRL – 0723433, September 1, 2007 – August 31, 2010, $590,044.

The Environment as a Context for Opportunities in Schools, Research Coordinator – NIH/National Institute for Environmental Health Sciences, grant R25 ES10698-01, September 15, 2000 – August 31, 2007, $1,348,482.

Bioscience Inspiration and Opportunities for Students, Research Coordinator – NIH/National Heart, Lung, and Blood Institute, grant R25 Hl075747, October 1, 2003 – September 30, 2008, $1,340,336.

MicroMatters, Research Coordinator – Science Education Partnership Award, grant R25 RR018605, July 1, 2003 – June 30, 2008, $1,618,008.

Science Education Leadership Fellows Project, Research Coordinator – Howard Hughes Medical Institute grant, October 1, 1999 – September 30, 2003, $539,714.

From Outer Space to Inner Space, Research Coordinator – National Space Biomedical Research Institute, grant NCC9-58, $226,093.

Filling the Gaps:  K-6 Science/Health Education, Research Coordinator – National Institutes of Health, National Center for Research Resources (NCRR) grant R25 RR13454, July 1, 1998 – June 30, 2001, $632,444.

Baylor Science Leadership Program, Research Coordinator – National Science Foundation/Houston Independent School District subcontract.
June 1, 1999 – May 31, 2000, $185,000
June 1, 2000 – May 31, 2001, $210,000

Beyond Bridging the Gap: Implementing a Model for Participatory Research and Development, Research Coordinator – U.S. Department of Education, 1996 – 1999, $500,000.

Selected Publications

Hox, J. J. & Roberts, J. K. (Eds.) (2011). Handbook of Advanced Multilevel Analysis. New York, NY:  Routledge.

Lane, F. C., Nimon, K. F. & Roberts, J. K. (2013). Random intercepts model of part-time employment and standardized testing using SPSS. In G. David Garson (Ed.), Hierarchical Linear Modeling: Guide and Applications. Thousand Oaks, CA:  Sage.

Hox, J. J. & Roberts, J. K. (2011).  Multilevel analysis:  Where we were and where we are. In J. J. Hox and J. Kyle Roberts (Eds.), Handbook of Advanced Multilevel Analysis. New York, NY:  Routledge.

Roberts, J. K., Monaco, J. P., Stovall, H. & Foster, V. (2011).  Explained variance in multilevel models. In J. J. Hox and J. Kyle Roberts (Eds.), Handbook of Advanced Multilevel Analysis. New York, NY:  Routledge.

Roberts, J. K., Nimon, K., & Martin, L. (2010).  Hierarchical linear modeling (HLM) applications in the context of giftedness research.  In B. Thompson & R. Subotnik (Eds.), Research Methodologies for Conducting Research on Giftedness.  Washington, DC:  American Psychological Association.

Roberts, J. K. & McLeod, P. (2008).  Software options for multilevel models.  In A. O’Connell & B. McCoach (Eds.), Multilevel Analysis of Educational Data.  Greenwich, CT:  Information Age Publications.

Henson, R. K. & Roberts, J. K. (2006). Exploratory factor analysis reporting practices in published psychological research:  Common errors and some comment on improved practice.  Educational and Psychological Measurement, 66(3), 393-416.

Roberts, J. K. & Herrington, R. (2005).  Demonstration of software programs for estimating multilevel measurement model parameters.  Journal of Applied Measurement, 6(3), 255-272.

Onwuegbuzie, A. J., Roberts, J. K., & Daniel, L. G. (2005).  A proposed new what if reliability analysis for assessing the statistical significance of bivariate relationships.  Measurement and Evaluation in Counseling and Development, 37(4), 228-239.

Roberts, J. K. & Fan, X. (2004).  Bootstrapping within the multilevel/hierarchical linear modeling framework:  A primer for use with SAS and S-PLUS.  Multiple Linear Regression Viewpoints, 30 (1), 23-34.







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