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Journal of Quantitative Analysis in Sports

An official journal of the American Statistical Association

Editor-in-Chief: Glickman, PhD, Mark / Rigdon, Steve

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Is high-altitude mountaineering Russian roulette?

Edward K. Cheng
  • Corresponding author
  • Vanderbilt University Law School, Nashville, TN 37203, USA; and Department of Statistics, Columbia University, New York, NY 10027, USA
  • Thanks to Jim Albert, Andreas Buja, Andrew Gelman, Ray Huey, David Madigan, Zach Shahn, and two anonymous reviewers for helpful comments and conversations. Research was conducted under Columbia University IRB protocol IRB-AAAF3302 (exempt) and supported by a Bedayn Research Grant from the American Alpine Club.
  • Email:
Published Online: 2013-03-30 | DOI: https://doi.org/10.1515/jqas-2012-0038


Whether the nature of the risks associated with climbing high-altitude (8000 m) peaks is in some sense “controllable” is a longstanding debate in the mountaineering community. Well-known mountaineers David Roberts and Ed Viesturs explore this issue in their recent memoirs. Roberts views the primary risks as “objective” or uncontrollable, whereas Viesturs maintains that experience and attention to safety can make a significant difference. This study sheds light on the Roberts-Viesturs debate using a comprehensive dataset of climbing on Nepalese Himalayan peaks. To test whether the data is consistent with a constant failure rate model (Roberts) or a decreasing failure rate model (Viesturs), it draws on Total Time on Test (TTT) plots from the reliability engineering literature and applies graphical inference techniques to them.

Keywords: 8000 m; mountaineering; survival analysis; total time on test (TTT); graphical inference


  • Andersen, P. K., O. Borgan, R. D. Gill, and N. Keiding. 1993. Statistical Models Based on Counting Processes. New York: Springer.Google Scholar

  • Barlow, R. and R. Campo. 1975. “Total time on test processes and applications to failure data analysis.” In: (R. Barlow, et al., eds.) Reliability and Fault Tree Analysis. Philadelphia: SIAM, 451–481.Google Scholar

  • Bender, R., T. Augustin, and M. Blettner. 2005. “Generating Survival Times to Simulate Cox Proportional Hazards Models.” Statistics in Medicine 24: 1713–1723. (URL http://dx.doi.org/10.1002/sim.2059).Web of ScienceCrossref

  • Boyce, J. R. and D. P. Bischak. 2010. “Learning by Doing, Knowledge Spillovers, and Technological and Organizational Change in Highaltitude Mountaineering.” Journal of Sports Economics, 11: 496–532 (URL http://jse.sagepub.com/content/11/5/496.abstract).Web of ScienceCrossref

  • Brillinger, D. R. 2008. “The 2005 Neyman Lecture: Dynamic Indeterminism.” Science 23: 48–64.Web of ScienceGoogle Scholar

  • Buja, A., D. Cook, H. Hofmann, M. Lawrence, E.-K. Lee, D. F. Swayne, and H.Wickham. 2009. “Statistical Inference for Exploratory Data Analysis and Model Diagnostics.” Philosophical Transactions of the Royal Society of London Series A-Mathematical Physical and Engineering Sciences 367: 4361–4383.Google Scholar

  • Burtscher, M., M. Philadelphy, W. Nachbauer, and R. Likar. 1995. “The Risk of Death to Trekkers and Hikers in the Mountains.” Journal of the American Medical Association 273: 460.Google Scholar

  • Davies, P. 2008. “Approximating Data.” Journal of the Korean Statistical Society 37: 199–200.Google Scholar

  • Firth, P. G., H. Zheng, J. S. Windsor, A. I. Sutherland, C. H. Imray, G. W. K. Moore, J. L. Semple, R. C. Roach, and R. A. Salisbury. 2008. “Mortality on Mount Everest, 1921–2006: Descriptive Study.” British Medical Journal 337: a2654.Web of ScienceGoogle Scholar

  • Hoyland, A. and M. Rausand. 1994. System Reliability Theory: Models and Statistical Methods. Hoboken, NJ: Wiley-Interscience.Google Scholar

  • Huey, R. B. 2001. “Mountaineering in thin air.” In: (R. C. Roach, ed.) Hypoxia: From Genes to the Bedsite. New York: Kluwer Academic. p. 225.Google Scholar

  • Huey, R.B. and X. Eguskitza. 2000. “Supplemental Oxygen and Mountaineer Death Rates on Everest and k2.” Journal of the American Medical Association 284: 181.Google Scholar

  • Huey, R. B. and X. Eguskitza. 2001. “Limits to Human Performance: Elevated Risks on High Mountains.” Journal of Experimental Biology 204: 3115–3119. (URL http://jeb.biologists.org/content/204/18/3115.abstract).

  • Huey, R. B., R. Salisbury, J.-L. Wang, and M. Mao. 2007. “Effects of Age and Gender on Success and Death of Mountaineers on Mount Everest.” Biology Letters 3: 498–500 (URL http://rsbl.royalsocietypublishing.org/content/3/5/498.abstract).

  • Ilgner, A. 2003. The Rock Warrior’s Way: Mental Training for Climbers. La Vergne, TN: Desiderata.Google Scholar

  • Jolly, J. 2010. “Elizabeth Hawley, unrivalled Himalayan record keeper,” (URL http://www.bbc.co.uk/news/world-south-asia-10268549). Accessed on March 6, 2013.

  • Pollard, A. and C. Clarke. 1988. Deaths During mountaineering at extreme altitude, The Lancet, 331, 1277.Google Scholar

  • Roberts, D. 2005. On the Ridge Between Life and Death. New York: Simon & Schuster.Google Scholar

  • Salisbury, R. 2003. The Himalayan Database: The Expedition Archives of Elizabeth Hawley. Golden, CO: American Alpine Club.Google Scholar

  • Salisbury, R. and E. Hawley. 2007. The Himalaya by the numbers: A statistical analysis of mountaineering in the Nepal Himalaya, (URL http://www.himalayandatabase.com/downloads/HimalayaByNbrs.pdf). Accessed on March 6, 2013.

  • Singer J. D. and J. B. Willett. 2003. Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. New York: Oxford.Google Scholar

  • Viesturs, E. and D. Roberts. 2006. No Shortcuts to the Top: Climbing the World’s 14 Highest Peaks. New York: Broadway.Google Scholar

  • Westhoff, J. L., T. D. Koepsell, and C. T. Littell. 2012. “Effects of Experience and Commercialisation on Survival in Himalayan Mountaineering: Retrospective Cohort Study.” British Medical Journal 344: e3782.Web of ScienceGoogle Scholar

  • Windsor, J. S., P. G. Firth, M. P. Grocott, G. W. Rodway, and H. E. Montgomery. 2009. “Mountain mortality: a review of deaths that occur during recreational activities in the mountains.” Postgraduate Medical Journal 85: 316–321, (URL http://pmj.bmj.com/content/85/1004/316.abstract).Web of Science

About the article

Corresponding author: Edward K. Cheng, Vanderbilt University Law School, Nashville, TN 37203, USA; and Department of Statistics, Columbia University, New York, NY 10027, USA

Published Online: 2013-03-30

This 60% figure would appear to come from


Further extensions of the method might involve outsourcing the visual processing to external observers, such as those provided by a service like Amazon Mechanical Turk (mTurk) (Buja et al. 2009: 4381). Amazon mTurk is particularly useful for testing at p-values lower than 0.05, since there are limits to the number of graphs a person can simultaneously compare, and space (and boredom) limitations preclude including pages of plots in journals.

TTT plots for ascent rates would necessarily require different calculations than those proposed in this Article, because climbers can have multiple ascents. Unlike death, success does not censor further observation of a climber.

Citation Information: Journal of Quantitative Analysis in Sports, ISSN (Online) 1559-0410, ISSN (Print) 2194-6388, DOI: https://doi.org/10.1515/jqas-2012-0038.

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