Coherence and Focused Hypotheses

  • Paul R. Rosenbaum
Part of the Springer Series in Statistics book series (SSS)


The 1964 US Surgeon General’s report, Smoking and Health (Bayne-Jones et al. 1964, p. 20), lists five criteria for judgment about causality, the fifth being “the coherence of the association.” A single sentence defines coherence (Bayne-Jones et al. 1964, p. 185) :“A final criterion for the appraisal of causal significance of an association is its coherence with known facts in the natural history and biology of the disease.” There follows a long discussion of the many ways in which the association between smoking and lung cancer is coherent. Per capita consumption of cigarettes had, at that time, been increasing, and the incidence of lung cancer was also increasing. Men, at that time, smoked much more than women and had a much higher incidence of lung cancer. And so on. To this, Sir Austin Bradford Hill (1965, p. 10) adds: “... I regard as greatly contributing to coherence the histopathological evidence from the bronchial epithelium of smokers and the isolation from cigarette smoke of factors carcinogenic for the skin of laboratory animals.” The pattern of associations in §1.2 between smoking and cardiovascular disease would also be described as coherent. Coherence is discussed by Susser (1973, pp. 154–162) and more critically by Rothman (1986, p. 19) . MacMahon and Pugh (1970, p. 21) use the phrase “consonance with existing knowledge” in place of coherence. Coherence is related to Fisher’s “elaborate theory,” as discussed in §1.2.


Coherent Statistic Signed Rank Sister Chromatid Exchange Coherent Pattern Bibliographic Note 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Allison, P. D. (1990) Change scores as dependent variables in regression analyses. In: Sociological Methodology, C. C. Clogg, ed., Oxford: Basil Blackwell, pp. 93–114.Google Scholar
  2. Allison, P. D. and Long, J. S. (1990) Departmental effects on scientific productivity. American Sociological Review, 55, 469–478.CrossRefGoogle Scholar
  3. Barlow, R., Bartholomew, D., Bremner, J., and Brunk, H. (1972) Statistical Inference Under Order Restrictions. New York: Wiley.zbMATHGoogle Scholar
  4. Bayne-Jones, S., Burdette, W., Cochran, W., Farber, E., Fieser, L., Furth, J., Hickman, J., LeMaistre, C., Schuman, L., and Seevers, M. (1964) Smoking and Health: Report of the Advisory Committee to the Surgeon General of the Public Health Service. Washington, DC: US Department of Health, Education, and Welfare.Google Scholar
  5. Campbell, D. and Stanley, J. (1963) Experimental and Quasi Experimental Designs for Research. Chicago: Rand McNally.Google Scholar
  6. Cook, T. D. (1991) Clarifying the warrant for generalized causal inferences in quasi-experimentation. In: Evaluation and Education at Quarter Century, M. W. McLaughlin and D. Phillips, eds., NSSE 1991 Yearbook, pp. 115–144.Google Scholar
  7. Cook, T. D., Campbell, D. T. and Peracchio, L. (1990) Quasi Experimentation. In: Handbook of Industrial and Organizational Psychology, M. Dunnette and L. Hough, eds., Palo Alto, CA: Consulting Psychologists Press, Chapter 9, pp. 491–576.Google Scholar
  8. Cook, T. D. and Shadish, W. R. (1994) Social experiments: Some developments over the past fifteen years. Annual Review of Psychology, 45, 545–580.CrossRefGoogle Scholar
  9. Davidson, D. (1986) A coherence theory of truth and knowledge. In: Truth and Interpretation, E. Lepore, ed., Oxford: Blackwell, pp. 307–319.Google Scholar
  10. Grevert, P. and Goldstein, A. (1977) Effects of naloxone on experimentally induced ischemic pain and on mood in human subjects. Proceedings of the National Academy of Sciences (Psychology), 74, 1291–1294.CrossRefGoogle Scholar
  11. Hill, A. B. (1965) The environment and disease: Association or causation? Proceedings of the Royal Society of Medicine, 58, 295–300.Google Scholar
  12. Hoerauf, K., Lierz, M., Wiesner, G., Schroegendorfer, K., Lierz, P., Spacek, A., Brunnberg, L., Nusse, M. (1999) Genetic damage in operating room personnel exposed to isoflurane and nitrous oxide. Occupational and Environmental Health, 56, 433–437.Google Scholar
  13. Hollander, M., Proschan, F., and Sethuraman, J. (1977) Functions decreasing in transposition and their applications in ranking problems. Annals of Statistics, 5, 722–733.MathSciNetzbMATHCrossRefGoogle Scholar
  14. Hollander, M. and Wolfe, D. (1973) Nonparametric Statistical Methods. New York: Wiley.zbMATHGoogle Scholar
  15. Hsu, J. C., Hwang, J. T. G., Liu, H. K., and Ruberg, S. J. (1994) Confidence intervals associated with tests for bioequivalence. Biometrika, 81, 103–114.MathSciNetzbMATHCrossRefGoogle Scholar
  16. Jonckheere, A. (1954) A distribution-free k-sample test against ordered alternatives. Biometrika, 41, 133–145.MathSciNetzbMATHGoogle Scholar
  17. Li, Y., Propert, K. J. and Rosenbaum, P. R. (2001) Balanced risk set matching. Journal of the American Statistical Association, 96, September, to appear.Google Scholar
  18. Maclure, M. and Greenland, S. (1992) Tests for trend and dose-response: Misinterpretations and alternatives. American Journal of Epidemiology, 135, 96–104.Google Scholar
  19. MacMahon, B. and Pugh, T. (1970) Epidemiology: Principles and Methods. Boston: Little, Brown.Google Scholar
  20. Mann, H. and Whitney, D. (1947) On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics, 18, 50–60.MathSciNetzbMATHCrossRefGoogle Scholar
  21. Mantel, N. (1967) Ranking procedures for arbitrarily restricted observations. Biometrics, 23, 65–78.CrossRefGoogle Scholar
  22. Page, E. (1963) Ordered hypotheses for multiple treatments: A significance test for linear ranks. Journal of the American Statistical Association, 58, 216–230.MathSciNetzbMATHCrossRefGoogle Scholar
  23. Popper, K. (1965) Conjectures and Refutations. New York: Harper & Row.Google Scholar
  24. Popper, K. (1983) Realism and the Aim of Science. Totowa, NJ: Rowman and Littlefield.Google Scholar
  25. Robertson, T., Wright, F. T., and Dykstra, R. L. (1988) Order Restricted Statistical Inference. New York: Wiley.zbMATHGoogle Scholar
  26. Rosenbaum, P. R. (1991) Some poset statistics. Annals of Statistics, 19, 1091–1097.MathSciNetzbMATHCrossRefGoogle Scholar
  27. Rosenbaum, P. R. (1994) Coherence in observational studies. Biometrics, 50, 368–374.zbMATHCrossRefGoogle Scholar
  28. Rosenbaum, P. R. (1997) Signed rank statistics for coherent predictions. Biometrics, 53, 556–566.zbMATHCrossRefGoogle Scholar
  29. Rosenbaum, P. R. (2001) Stability in the absence of treatment. Journal of the American Statistical Association, 96, 210–219.MathSciNetzbMATHCrossRefGoogle Scholar
  30. Rothman, K. (1986) Modern Epidemiology. Boston: Little, Brown.Google Scholar
  31. Salzberg, A. (1999) Removable selection bias in quasi-experiments. The American Statistician, 53, 103–107.Google Scholar
  32. Schuirmann, D. J. (1987) A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability. Journal of Pharmacokinetics and Biopharmaceutics, 15, 657–680.Google Scholar
  33. Shadish, W. R., Cook, T. D., and Campbell, D. T. (2002) Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Boston: Houghton-Mifflin.Google Scholar
  34. Skerfving, S., Hansson, K., Mangs, C., Lindsten, J., and Ryman, N. (1974) Methylmercury-induced chromosome damage in man. Environmental Research, 7, 83–98.CrossRefGoogle Scholar
  35. Susser, M. (1973) Causal Thinking in the Health Sciences. New York: Oxford University Press.Google Scholar
  36. Susser, M. (1991) What is a cause and how do we know one? A grammar for pragmatic epidemiology. American Journal of Epidemiology, 133, 635–648.Google Scholar
  37. Thagard, P. (2000) Coherence in Thought and Action. Cambridge, MA: MIT Press.Google Scholar
  38. Wilcoxon, F. (1945) Individual comparisons by ranking methods. Biometrics, 1, 80–83.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Paul R. Rosenbaum
    • 1
  1. 1.Department of Statistics, The Wharton SchoolUniversity of PennsylvaniaPhiladelphiaUSA

Personalised recommendations