Jason W. Beckstead, PhD
Associate Professor
 
E-mail: jbeckste@health.usf.edu Voicemail:(813) 974-7667
Website:Click here
Research Interests
  • An expert in quantitative methods, Dr. Beckstead works with colleagues on multiple projects including cardiac rehabilitation, biological basis for postpartum depression, assessment of moral reasoning skills among healthcare providers, and the psychology of rumor transmission. He is also Statistical Editor for the International Journal of Nursing Studies.
  • Judgment and Decision-Making
  • Development and Application of Quantitative Methods in Healthcare Research

Educational Background
  • B.S. in Psychology, 1983, University of Oklahoma, Oklahoma City, OK.
  • Ph.D. in Experimental Psychology, 1990, State University of New York at Albany
  • Post Doctoral Research Associate, 1990-1993, Rensselaer Polytechnic Institute, Troy, NY.
Recent Publications
  • Beckstead, J.W. (2012). Isolating and examining sources of suppression and multicollinearity in multiple linear regression. Multivariate Behavioral Research, 47, 224-246.
  • Beckstead, J.W. (2009). Content validity is naught. International Journal of Nursing Studies, 46(9), 1274-1283.
  • Beckstead, J.W. (2008). Modeling sequential context effects in judgment analysis: A time series approach. Judgment and Decision Making, 3(7), 570-584.
  • Beckstead, J.W., Yang, C.Y., & Lengacher, C.A. (2008). Assessing cross-cultural validity of scales: A methodological review and illustrative example. International Journal of Nursing Studies, 45, 110-119.
  • Beckstead, J.W. (2007). A note on determining the number of cues used in judgment analysis studies: the issue of type II error. Judgment and Decision Making, 2 (5), 317-325.
  • Beckstead, J.W., & Stamp, K.D. (2007). Understanding how nurse practitioners estimate patients' risk for coronary heart disease: A judgment analysis. Journal of Advanced Nursing, 60 (4), 436-446.
  • Beckstead, J.W., & Beckstead, L.G. (2006). A multidimensional analysis of the epistemic origins of nursing theories, models, and frameworks. International Journal of Nursing Studies, 43, 113-122.