Bio

Jason W Osborne joined Miami University in 2019 as a Professor of Statistics, Provost and Executive Vice President for Academic Affairs. He currently serves as Professor and Chair of the Department of Statistics.

As an educational psychologist, Jason W Osborne concentrates on factors linked to equitable achievement and student success. This includes the impact of environmental and socio-cultural impacts on achievement gaps and the relationship between persistence and success in education, using real world data as a valuable tool for quantitative analysis.

Specialties include data science, evaluation, clinical outcomes, best practices in quantitative data analysis, data informatics, applied statistics, statistical consulting and social justice.

In 2013, Jason W Osborne was awarded a PSTAT (Accredited Professional Statistician) by the American Statistical Association. The award recognized Dr. Osborne’s expertise as a globally-cited author in data analysis, educational psychology, statistics, best practices in quantitative methods, and applying a practitioner oriented look in evidence-based research methods using influential data points to predict important outcomes.

Professional activities and faculty positions

Positions prior to Jason W Osborne joining Miami University, including as a faculty member and in leadership roles in recent years:

2015-2019: Associate Provost, Dean of the Graduate School and Professor of Statistics at Clemson University. Using his background in educational psychology and world class research methods, Jason W Osborne championed inclusivity, grew graduate and professional higher education across the university, and expanded internal and extramural funding.

2013-2015: Department Chair and Professor at the University of Louisville, (KY). Jason Osborne served as Chair of Counseling and Human Development and Interim Chair of Health and Sport Sciences. Jason W Osborne was also a leader in development of service and engagement initiatives, including establishment of the Cardinal Success Program, which provided mental health and wellness services free of charge to the most underserved areas of the city. He also published extensively on modern research methods and applied evidence-based best practices in data analysis and quantitative methods.

2011-2013: Associate Professor, Old Dominion University where he served as departmental director of graduate programs. Joining in the fall semester Jason W Osborne taught statistics and research methods and applied these skills through mentoring of faculty and students in the Educational Foundations and Leadership programs.

2001- 2011: Assistant/Associate Professor, Graduate Program Coordinator at North Carolina State University in Educational Psychology, Department of Curriculum and Instruction and Counselor Education.

1998-2001: Assistant Professor at the University of Oklahoma across the particular domains of Statistics and Research Methods in the Department of Educational Psychology.

Recent Awards and Honors

2021, 2023: Named in the Top 2% of researchers in the world by Stanford University, highlighting his commitment to world-class research methods and data recording.

2018: University Research, Scholarship and Artistic Achievement Award as Clemson University Professor of Educational Psychology Statistics.

2017: Best Paper from the American Counseling Association for his book “Best Practices in Data Cleaning: How Outliers and “Fringeliers” Affect Your Analysis”.

2016: Presidential Service Award by Clemson University Graduate School for recognition of contributions to students in higher education.

2015: Faculty Favorite, Outstanding Teaching Award, University of Louisville

2013: Accredited Professional Statistician (PSTAT) from the American Statistical Association.

Publications – books

2017: Regression and Linear Modeling: Best practices and modern methods. Thousand Oaks, CA: SAGE Publishing. ISBN #978-1-50630-276-8

2016: With Banjanovic, E. Exploratory factor analysis using SAS: Best practices and modern methods. Cary, NC: SAS Publishing. ISBN # 978-1-62960-064-2

2015: Best practices in logistic regression. Thousand Oaks, CA: SAGE Publishing. ISBN 978-1-4522-4479-2.

2014: Best Practices in Exploratory Factor Analysis. Scotts Valley, CA: CreateSpace Independent Publishing. ISBN-13: 978-1500594343, ISBN-10:1500594342.

2013: Sweating the Small Stuff: Does data cleaning and testing of assumptions really matter in the 21st century? Lausanne, Switzerland: Frontiers Research Foundation. ISBN 978-2-88919-155-0.

2013a: Best practices in data cleaning: A complete guide to everything you need to do before and after collecting your data. Thousand Oaks, CA: SAGE Publishing. ISBN: 9781412988018. Translated into Arabic by International Publishers Association (IPA), Geneva Switzerland.

2008: Best practices in quantitative methods. Thousand Oaks, CA: SAGE Publishing. Included in SAGE Research Methods Online). ISBN: 9781412940658

Select recent Publications – peer reviewed

Adelson, J., Osborne, J. W., & Crawford, B. J. (2019). Correlation and other measures of association. In G. Hancock, L. Stapleton, & R. Mueller (Eds.) The Reviewer’s Guide to Quantitative Methods in the Social Sciences, 2nd edition. New York, NY: Routledge.

Gabel, C. P., Moktarinia, H., Hoffman, J., Osborne, J., Laakso, L., & Melloh, M. (2018). Does the performance of five back-associated exercises relate to the presence of low back pain? A cross-sectional observational investigation in regional Australian council workers. British Medical Journal Open, 8, 1-11. doi: 10.1136/bmjopen-2017-020946

Osborne, Jason W. (2017). Best practices: A moral imperative. Canadian Journal of Behavioral Science, 49(3), 153-158.

Balkin, R. S., Richey Gosnell, K. M., Holmgren, A., & Osborne, J. W. (2017). Nonlinear analysis in counseling research. Measurement and Evaluation in Counseling and Development, 50, 109-155. Recipient of Patricia B. Elmore Award for Outstanding Research in Measurement by the American Counseling Association.

*Pitts, C. H., Klein-Tasman, B. P., Osborne, J. W., Mervis, C.B. (2016). Predictors of Specific Phobia in Children with Williams Syndrome: Behavior Regulation and IQ. Journal of Intellectual Disability Research, 60(10), 1031-1042.

Clark, J. E., Osborne, J. W., Gallagher, P., & Watson, S., (2016). A simple method for optimizing transformation of non-parametric data: An illustration by reference to cortisol assays. Human Pharmacology: Clinical and Experimental, 31(4), 259-267. DOI: 10.1002/hup.2528

Gabel, C. P., Cuesta-Vargas, A., Barr, S., Winkeljohn-Black, S. Osborne, J. W., & Melloh, M. (2016). Confirmatory factor analysis of the neck disability index, comparing patients with whiplash associated disorders to a control group with non-specific neck pain. European Spine Journal, 14(8), 1410-1416. http://www.ncbi.nlm.nih.gov/pubmed/27040281

Banjanovic, E. A., & Osborne, J. W. (2016). Confidence intervals for effect sizes: Applying bootstrap resampling. Practical Assessment, Research, and Evaluation, 21(5a), 1-20. http://pareonline.net/getvn.asp?v=21&n=5

Jones, B. D., *Ruff, C., & Osborne, J. W. (2015). Fostering students’ identification with mathematics and science using principles from the MUSIC model of academic motivation. In K. A. Renninger, M. Nieswandt, & S. Hidi (Eds.), Interest in Mathematics and Science Learning. Washington, DC: American Educational Research Association.

Osborne, Jason W. (2015). What is rotating in exploratory factor analysis? Practical Assessment, Research, and Evaluation, 20(2), 1-7