Leadership in Statistics: Increasing Our Value and Visibility

References

• Bailar, B. (1988), “Statistical Practice and Research: The Essential Interactions,” Journal of the American Statistical Association, 83, 1–8.
   Web of Science ®Google Scholar
• Begg, M. D., and Vaughan, R. D. (2011), “Are Biostatistics Students Prepared to Succeed in the Era of Interdisciplinary Science? (And How Will We Know?),” The American Statistician, 65, 71–79.
   Web of Science ®Google Scholar
• Blair, R., Kirkman, E. E., and Maxwell, J. W. (2013), Statistical Abstract of Undergraduate Programs in the Mathematical Sciences in the United States: Fall 2010 CBMS Survey, Washington, DC: Mathematical Association of America. Available at https://www.ams.org/profession/data/cbms-survey/cbms2010-Report.pdf
   Google Scholar
• Box, G. E. P. (1976), “Science and Statistics,” Journal of the American Statistical Association, 71, 791–799.
   Web of Science ®Google Scholar
• Breiman, L. (2001), “Statistical Modeling: The Two Cultures,” ( with discussion), Statistical Science, 16, 199–231.
   Web of Science ®Google Scholar
• Bretz, F., Pinheiro, J., and Branson, M. (2005), “Combining Multiple Comparisons and Modeling Techniques in Dose Response Studies,” Biometrics, 61, 738–748.
   PubMed Web of Science ®Google Scholar
• Brown, E., and Kass, R. (2009), “What is Statistics?” (with discussion), The American Statistician, 63, 105–123.
   Web of Science ®Google Scholar
• Buchanich, J. M. (2012), “Scientific Course Strengthens Students’ Communication Skills,” Amstat News, 416, 7.
   Google Scholar
• Cleveland, W. S. (2001), “Data Science: An Action Plan for Expanding the Technical Areas of the Field of Statistics,” International Statistical Review, 69, 21–26.
   Web of Science ®Google Scholar
• Cox, D. R. (1997), “The Current Position of Statistics: A Personal View,” International Statistical Review, 65, 261–290.
   Web of Science ®Google Scholar
• Davidian, M., and Louis, T. A. (2012), “Why Statistics?” Science, 336, 12.
   PubMed Web of Science ®Google Scholar
• DeMets, D. L., Stormo, G., Boehnke, M., Louis, T. A., Taylor, J., and Dixon, D. (2006), “Training of the Next Generation of Biostatisticians: A Call to Action in the U.S,” Statistics in Medicine, 25, 3415–3429.
   PubMed Web of Science ®Google Scholar
• Deming, W. E. (1965), “Principles of Professional Statistical Practice,” Annals of Mathematical Statistics, 36, 1883–1900.
   Google Scholar
• EMA (2014), Qualification Opinion of MCP-Mod as an Efficient Statistical Methodology for Model-Based Design and Analysis of Phase II Dose Finding Studies Under Model Uncertainty. EMA Doc. Ref. EMA/CHMP/SAWP/757052/2013. Available at http://www.ema.europa.eu/docs/en_GB/document_library/Regulatory_and_procedural_guideline/2014/02/WC500161027.pdf
   Google Scholar
• FDA (2016), Fit-For-Purpose Determination of the MCP-Mod Method for Dose Finding. Available at http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/UCM508700.pdf.
   Google Scholar
• Geller, N. L. (2011), “Statistics: An All-Encompassing Discipline,” Journal of the American Statistical Association, 106, 1225–1229.
   Web of Science ®Google Scholar
• Hand, D. J. (2009), “Modern Statistics: The Myth and the Magic,” Journal of the Royal Statistical Society, Series A, 172, 287–306.
   Web of Science ®Google Scholar
• Iman, R. L. (1995), “New Paradigms for the Statistics Profession,” Journal of the American Statistical Association, 90, 1–6.
   Web of Science ®Google Scholar
• Keller-McNulty, S. (2007), “From Data to Policy,” Journal of the American Statistical Association, 102, 395–399.
   Web of Science ®Google Scholar
• Kettenring, J. R. (1997), “Shaping Statistics for Success in the 21st Century,” Journal of the American Statistical Association, 92, 1229–1234.
   Web of Science ®Google Scholar
• Kowalski, K. G. (2015), “My Career as a Pharmacometrician and Commentary on the Overlap Between Statistics and Pharmacometrics in Drug Development,” Statistics in Biopharmaceutical Research, 7, 148–159.
   Web of Science ®Google Scholar
• LaVange, L., Sollecito, W., Steffen, D., Evarts, L., and Kosorok, M. (2012), “Preparing Biostatisticians for Leadership Opportunities,” Amstat News, 416, 5–6.
   Google Scholar
• LaVange, L. (2014), “The Role of Statistics in Regulatory Decision Making,” Therapeutic Innovation and Regulatory Science, 48, 10–19.
   PubMed Web of Science ®Google Scholar
• Lazar, N. A., Reeves, J., and Franklin, C. (2011), “A Capstone Course for Undergraduate Statistics Majors,” The American Statistician, 65, 183–189.
   Web of Science ®Google Scholar
• Lindsay, B. G., Kettenring, J., and Siegmund, D. O. (2004), “A Report on the Future of Statistics,” Statistical Science, 19, 387–413.
   Web of Science ®Google Scholar
• Lohr, S. (August 5, 2009), “For Today's Graduate, Just One Word: Statistics,” New York Times.
   Google Scholar
• Madigan, D., and Wasserstein, R. (eds.) (2014), Statistics and Science: A Report of the London Workshop on the Future of the Statistical Sciences. Available at http://bit.ly/londonreport
   Google Scholar
• Manyika, J., Chui, M., Brown, B., Bughin, J., Doobs, R., Roxburgh, C., and Byers, A. (2011), Big Data: The Next Frontier for Innovation, Competition, and Productivity, The McKinsey Global Institute, McKinsey & Company. Available at http://www.mckinsey.com/mgi
   Google Scholar
• Marquardt, D. W. (1987), “The Importance of Statisticians,” Journal of the American Statistical Association, 82, 1–7.
   Web of Science ®Google Scholar
• ——— (1979), “Statistical Consulting in Industry,” The American Statistician, 33, 102–107.
   Web of Science ®Google Scholar
• Matloff, N. (2014), “Statistics Losing Ground to Computer Science,” Amstat News, 449, 25–26.
   Google Scholar
• McNutt, M. (2014), “Raising the Bar,” Science, 345, 9.
   PubMed Web of Science ®Google Scholar
• Meng, X. (2009), “Desired and Feared: What Do We Do Now and Over the Next 50 Years?” The American Statistician, 63, 202–210.
   Web of Science ®Google Scholar
• Moore, D. S. (1998), “Statistics Among the Liberal Arts,” Journal of the American Statistical Association, 98, 1253–59.
   Google Scholar
• Morganstein, D. (2015), “Statistics: Making Better Decisions,” Journal of the American Statistical Association, 110, 1325–1330.
   Web of Science ®Google Scholar
• Morton, S. C. (2010), “Statistics: From Evidence to Policy,” Journal of the American Statistical Association, 105, 1–5.
   Web of Science ®Google Scholar
• Mulvey, T., Esen E., and Schramm, J. (2016), Jobs of the Future: Data Analysis Skills, SHRM Survey Findings, Society for Human Resource Management. Available at http://www.amstat.org/asa/files/pdfs/Data-Analysis-Skills_SHRM_Survey.pdf
   Google Scholar
• Myers, J. (2015), “Public Relations Campaign Now in Second Year,” AmStat News, 452, 26–28.
   Google Scholar
• Nixon, R., Dierig, C., Mt-Isa, S., Stockert, I., Tong, T., Kuhls, S., Hodgson, G., Pears, J., Waddingham, E., Hockley, K., and Thomson, A. (2016), “A Case Study Using the Proact-URL, and BRAT Frameworks for Structured Benefit Risk Assessment,” Biometrical Journal, 58, 8–27.
   PubMed Web of Science ®Google Scholar
• Norwood, J. L. (1990), “Statistics and Public Policy: Reflections of a Changing World,” Journal of the American Statistical Association, 85, 1–5.
   PubMed Web of Science ®Google Scholar
• Pantula, S. G., Teugels, J., and Stefanski, L. (2010), “A Statistical Education,” Science News, 177(10), 32.
   Google Scholar
• Pierson, S. (2015), “Statistics Degrees Continue Strong Growth,” AmStat News, 460, 10.
   Google Scholar
• Rao, C. R. (2001), “Statistics: Reflections on the Past and Visions for the Future,” Communications in Statistics—Theory and Methods, 30, 2235–2257.
   Web of Science ®Google Scholar
• Rodriguez, R. (2012a), “Statistical Leadership—Preparing Our Future Leaders,” Amstat News, 416, 3–4.
   Google Scholar
• ——— (2012b), “A Major Trend: The Rise of Undergraduate Programs in Statistics,” Amstat News, 422, 3–4.
   Google Scholar
• ——— (2012c), “Career Success Training for Statisticians: An Update,” Amstat News, 424, 3–4.
   Google Scholar
• ——— (2013), “Building the Big Tent for Statistics,” Journal of the American Statistical Association, 108, 1–6.
   Web of Science ®Google Scholar
• ——— (2015), “Who Will Celebrate Our 200th Anniversary? Growing the Next Generation of ASA Members,” The American Statistician, 69, 91–95.
   Web of Science ®Google Scholar
• Rosling, H., and Zhang, Z. (2011), “Health Advocacy with Gapminder Animated Statistics,” Journal of Epidemiology and Global Health, 1, 11–14.
   PubMedGoogle Scholar
• Siegfried, T. (2010), “Odds Are, Its Wrong,” Science News, 177(7), 26.
   Google Scholar
• Speed, T. (2014), “Trilobites and Us,” Amstat News, 439, 9–10.
   Google Scholar
• Sutton, A. J., and Higgins, J. P. T. (2008), “Recent Developments in Meta-analysis,” Statistics in Medicine, 27, 625–650.
   PubMed Web of Science ®Google Scholar
• Tukey, J. W. (1980), “We Need Both Exploratory and Confirmatory,” The American Statistician, 34, 23–25.
   Web of Science ®Google Scholar
• Utts, J. (2015), “The Many Facets of Statistics Education: 175 Years of Common Themes,” The American Statistician, 69, 100–107.
   Web of Science ®Google Scholar
• Wasserstein, R. (2015), “Communicating the Power and Impact of Our Profession: A Heads Up for the Next Executive Directors of the ASA,” The American Statistician, 69, 96–99.
   Web of Science ®Google Scholar
• Wasserstein, R., and Lazar, N. (2016), “The ASA's Statement on p-Values: Context, Process, and Purpose,” The American Statistician, 70, 129–133.
   Web of Science ®Google Scholar
• Zelen, M. (2003), “The Training of Biostatistical Scientists,” Statistics in Medicine, 22, 3427–3430.
   PubMed Web of Science ®Google Scholar