- About Us
- Consulting & Tutoring
My primary research is as an applied statistician/biostatistician working on collaborative projects. I greatly enjoy the opportunity this affords me to learn new things about many different fields and disciplines. A very small sample of research I have had the fortune to support includes perinatal outcomes, diabetes, physical fitness, physical therapy, orthopedic surgery, anesthesia, infectious disease spread and diagnosis, sports analytics, traumatic brain injury and heart disease. I have particular interest in statistical modeling of categorical data, logistic regression, and survival analysis. Additional research interests involve statistical and mathematical education. A particularly fun aspect of this latter pursuit is the use of games for teaching statistics.
I am a retired U.S. Army Colonel, and served on active duty for 27-years after graduating from West Point. I completed my military service at West Point after I was selected as an Academy Professor. During this time, I founded and directed the West Point Center of Data Analysis and Statistics (CDAS) and earned the academic rank of Professor of Applied Statistics. After retirement I spent time as Associate Professor of Clinical Public Health in the Biostatistics Division of the College of Public Health at The Ohio State University, where I also served briefly as Chair for Biostatistics. I then took a position as Professor at Azusa Pacific University, building and directing a new M.S. in Applied Statistics and Analytics. Most recently, I worked as a research biostatistician for the Henry M. Jackson Foundation for the Advancement of Military Medicine supporting research at the Uniformed Services University of Health Sciences. I am married to Mandy and have two children: Chelsea (Grove City College, 2009), and Steven (Baylor, 2016). Chelsea has two sons, Erik and Marcus. I enjoy playing the violin and running, not at the same time.
Thomas, D.M., Sturdivant, R., Dhurandhar, N.V., Debroy, S., and Clark, N. (2020) “A primer on COVID-19 Mathematical Models,” Obesity, 28(8), 1375-1377, doi:10.1002/oby.22881
Cameron, K.L., Tennent, D., Sturdivant, R.X., Posner, M.A., Peck, K.Y., Campbell, S.E., Westrick, R.B, and Owens, B.D. (2019) “Increased Glenoid Retroversion is Associated with Increased Rotator Cuff Strength in the Shoulder,” The American Journal of Sports Medicine 47(8), 1893-1900.
Özkale, M.R., Lemeshow, S., and Sturdivant, R. (2018) “Logistic regression diagnostics in ridge regression,” Computational Statistics 33(2): 563 – 593. doi: https://doi.org/10.1007/s00180-017-0755-x
Sturdivant, R. X., Pardoe, I., Berrier, J., and Watts, K. (2016) Statistics for Data Analytics, additional contributors: Vahid, F., Chan, C., and Nestler, S. Zyante, Inc. (zyBooks.com).
Kuiper, S. and Sturdivant, R. (2015) “Using Online Game-Based Simulations to Strengthen Students’ Understanding of Practical Statistical Issues in Real-Word Data Analysis,” The American Statistician, doi: 10.1080/00031305.2015.1075421
Hosmer, D. W., Lemeshow, S., and Sturdivant R. X. (2013) Applied Logistic Regression, Third Edition, Wiley, Inc., New Jersey. Over 60,000 citations (Google Scholar)
Cummiskey, K., Kuiper, S., and Sturdivant, R. (2012) “Using classroom data to teach students about data cleaning and testing assumptions,” Frontiers in Quantitative Psychology and Measurement, 3(354), doi: 10.3589/fpsyg.2012.00354.
Sturdivant, R. and Watts, K. (2010) “Modeling an outbreak of anthrax,” PRIMUS, 20(4), 344–361.
Huber, M. and Sturdivant, R. (2010) “Building a model for scoring 20 or more runs in a baseball game,” The Annals of Applied Statistics, 4(2), 791–804.
Sturdivant, R., Dunham, P., and Jardine, R. (2009) “Preparing mathematics teachers for technology-rich environments,” PRIMUS, 19(2), 161–173.
Sturdivant, R., Rotella, J., and Russell, R. (2008) “A smoothed residual based goodness-of-fit statistic for nest-survival models,” Studies in Avian Biology, 34, 45–54.
Sturdivant, R. and Hosmer, D. (2007) “A smoothed residual based goodness-of-fit statistic for logistic hierarchical regression models,” Computational Statistics and Data Analysis, 51(8), 3898–3912.