402 Citations Questioning the Indiscriminate Use of
Null Hypothesis Significance Tests in Observational Studies

(Compiled by Bill Thompson:  thompson@uark.edu)
(updated 2/26/01)

In 1997, I compiled a list of articles, books, and book chapters that questioned the widespread use of null hypothesis significance tests (a.k.a. null hypothesis tests, significance tests) in scientific research.  My goal was to provide those unfamiliar with this debate with a list of citations that pointed out the myriad of problems associated with the indiscriminate use of null hypothesis tests.  For parity, I also compiled a list of references that supported, at least to a limited extent, the use of null hypothesis tests.

Ironically, null hypothesis testing as it is currently practiced is a hybridization of R. A. Fisher’s significance test and J. Neyman and E. Pearson’s null hypothesis test (hence the label “null hypothesis significance test”).  These two approaches were fundamentally different and were the source of heated debate between these two camps for many years (see Goodman 1993a for an excellent review of this historical debate).  I sincerely doubt that the melding of these two approaches would have been acceptable to either Fisher or Neyman and Pearson.

Both the original list of 326 citations and the current one of 402 citations are strong evidence that null hypothesis testing has been, and continues to be, at the forefront of debate within a number of disciplines, especially the Social Sciences (see special features with pro/con articles on this topic in Morrison and Henkel 1970; Journal of Experimental Education 1993 [volume 61, no. 4]; Psychological Science 1997 [volume 8, no. 1];  Harlow et al. 1997; Behavioral and Brain Sciences 1998 [volume 21, no. 2]; and Research in the Schools [volume 5, no. 2]).  Although in 1997 I noted a general lack of awareness of this debate within my own discipline of wildlife biology/ecology, there have recently been some rumblings here as well (e.g., see Cherry 1998, Johnson 1999, and Anderson et al. 2000).  I was fortunate to be involved with co-chairing, with Dr. Chris Ribic, a symposium on the use/misuse of null hypothesis testing in wildlife science during the Fifth Annual Conference of The Wildlife Society in Buffalo, NY on 26 September, 1998.  This brought this important topic to the attention of many wildlife biologists for the first time, and ultimately lead to Dr. Doug Johnson’s 1999 invited paper, which won the Outstanding Article award from The Wildlife Society.  Particularly noteworthy are the comments by the new editor of the Journal of Wildlife Management, Dr. Leonard Brennan, in the January 2001 issue (p. 172), in which he recommended that prospective authors “Focus on establishing a meaningful effect size” and “Avoid excessive use of P-values”.  Drs. David Anderson, Ken Burnham, and Doug Johnson have been (and continue to be) important drivers for these changes within the field of wildlife biology.

References

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2.  Altman, D. G.  S. M. Gore, M. J. Gardner, and S. J. Pocock.  1983.  Statistical guidelines for contributors to medical journals. British Medical Journal 286:1489-1493.

3.  Amery, W. K., M. Hoing, M. Debroye, and F. Dom.  1987.  Some comments on the use of statistics in the evaluation of drug trials in migraine.  Neuroepidemiology 6:220-227.

4.  Anderson, D. R., K. P. Burnham, and W. L. Thompson.  2000.  Null hypothesis testing: problems, prevalence, and an alternative. Journal of Wildlife Management 64:912-923.

5.  Anderson, W. T.  1992.  Trouble in paradigms: robobuyer versus the blob - part 2.  Marketing and Research Today 20(2):87-94.

6.  Anscombe, F. J.  1956.  Discussion on Dr. David's and Dr. Johnson's Paper.  Journal of the Royal Statistical Society, Series B 18:24-27.

7.  Bailar, J. C., and F. Mosteller.  1992.  Guidelines for statistical reporting in articles for medical journals: amplifications and explanations.  Pages 313-331 in J. C. Bailar and F. Mosteller, eds.  Medical uses of statistics.  Second ed.  New England Journal of Medicine Books, Boston, Mass.

8.  Bakan, D.  1966.  The test of significance in psychological research.  Psychological Bulletin 66:423-437.

9.  Bakan, D.  1967.  On method: toward a reconstruction of psychological investigation.   Jossey-Bass, Inc., San Francisco, Calif.  178pp.

10.  Bandt, C. L., and J. R. Boen.  1972.  A prevalent misconception about sample size, statistical significance, and clinical importance.  Journal of Periodontics 43:181-183.

11.  Barnard, G. A.  1992.  Statistics and OR - some needed interactions.  Journal of the Operational Research Society 43:787-795.

12.  Barndorff-Nielsen, O.  1977.  Discussion of D. R. Cox's paper.  Scandinavian Journal of Statistics 4:67-69.

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16.  Bellhouse, D. R.  1993.  Invited commentary: p values, hypothesis tests, and likelihood.  American Journal of Epidemiology 137:497-499.

17.  Berg, A. O.  1979.  Some non-random views of statistical significance.  Journal of Family Practice 8:1011-1014.

18.  Berger, J. O.  1986.  Are P-values reasonable measures of accuracy?  Pages 21-27 in I. S. Francis, B. F. J. Manly, and F. C. Lam, eds.  Pacific Statistical Congress.  Elsevier Science Publ. Co., New York, N.Y.

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22.  Berkson, J.  1942.  Tests of significance considered as evidence.  Journal of the American Statistical Association 37:325-335.

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24.  Binder, A.  1963.  Further considerations on testing the null hypothesis and the strategy and tactics of investigating theoretical models.  Psychological Review 70:107-115.

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28.  Borenstein, M.  1994.  The case for confidence intervals in controlled clinical trials.  Controlled Clinical Trials 15:411-428.

29.  Borenstein, M.  1997.  Hypothesis testing and effect size estimation in clinical trials.  Annals of Allergy, Asthma, & Immunology 78:5-16.

30.  Borenstein, M.  1998.  The shift from significance testing to effect size estimation. In N. Schooler, editor.  Comprehensive clinical psychology.  Volume 3: research methods. Pergamon, Oxford, U.K.

31.  Boring, E. G.  1919.  Mathematical versus scientific significance.  Psychological Bulletin 16:335-338.

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39.  Browner, W. S., and T. B. Newman.  1987.  Are all significant P values created equal?  The analogy between diagnostic tests and clinical research.  Journal of the American Medical Association 257:2459-2463.

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43.  Burnham, K. P., and D. R. Anderson.  1998.  Model selection and inference: a practical information-theoretic approach.  Springer-Verlag, New York, N.Y.  353pp.

44.  Cahan, S.  2000.  Statistical significance is not a “Kosher Certificate” for observed effects: a critical analysis of the two-step approach to the evaluation of empirical results.  Educational Researcher 29:31-34.

45.  Camilleri, S. F.  1962.  Theory, probability, and induction in social research.  American Sociological Review 27:170-178.

46.  Campillo, A. C.  1996.  [Erroneous interpretation of p values.] [Spanish]  Atencion Primaria 17:221-224.

47.  Capone, C. A., Jr., and S. L. Seaman.  1989.  Uses and misuses of hypothesis testing.  Journal of Business Forecasting Methods and Systems 8:18-27.

48.  Carver, R. P.  1978.  The case against statistical significance testing.  Harvard Educational Review 48:378-399.

49.  Carver, R. P.  1993.  The case against statistical significance testing, revisited.  Journal of Experimental Education 61:287-292.

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51.  Chatfield, C.  1985.  The initial examination of data (with discussion).  Journal of the Royal Statistical Society, Series A 148:214-253.

52.  Chatfield, C.  1989.  Comments on the paper by McPherson. Journal of the Royal Statistical Society, Series A 152:234-238.

53.  Chernoff , H.  1986.  Comment.  American Statistician  40:5-6.

54.  Cherry, S.  1998.  Statistical tests in publications of The Wildife Society. Wildlife Society Bulletin 26:947-953.

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56.  Chew, V.  1980.  Testing differences among means: correct interpretation and some alternatives.  HortScience 15:467-470.

57.  Cicchetti, D. V.  1998.  Role of null hypothesis significance testing (NHST) in the design of neuropsychologic research. Journal of Clinical and Experimental Neuropsychology 20:293-295.

58.  Clark, C. A.  1963.  Hypothesis testing in relation to statistical methodology.  Review of Educational Research 33:455-473.
 

59.  Clark, C. M.  1999.  Further considerations of null hypothesis testing.  Journal of Clinical and Experimental Neuropsychology 21:283-284.

60.  Coats, W.  1970.  A case against the normal use of inferential statistical models in educational research.  Educational Researcher (June):6-7.

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62.  Cohen, J.  1965.  Some statistical issues in psychological research.  Pages 95-121 in B. B. Wolman, ed.  Handbook of clinical psychology.  McGraw-Hill, New York, N.Y.

63.  Cohen, J.  1990.  Things I have learned (so far). American Psychologist 45:1304-1312.

64.  Cohen, J.  1994.  The earth is round (p<.05). American Psychologist 49:997-1003.

65.  Connolly, R. A.  1991.  A posterior odds analysis of the weekend effect.  Journal of Econometrics 49:51-104.

66.  Cooke, R. W., and A. M. Weindling.  1993.  Clinical trials and P values.  Pediatrics 92:188-189.

67.  Cormack, R. M.  1985.  Discussion of Dr. Chatfield's paper.  Journal of the Royal Statistical Society, Series A 148:231-233.

68.  Cowger, C. D.  1984.  Statistical significance tests: scientific ritualism or scientific method?  Social Service Review 58:358-372.

69.  Cox, D. R.  1958.  Some problems connected with statistical inference.  Annals of Mathematical Statistics 29:357-372.

70.  Cox, D. R.  1977.  The role of significance tests (with discussion).  Scandinavian Journal of Statistics 4:49-70.

71.  Cox, D. R.  1982.  Statistical significance tests. British Journal of Clinical Pharmacology 14:325-331.

72.  Cox, D. R.  1986.  Some general aspects of the theory of statistics.  International Statistical Review 54:117-126.

73.  Cox, D. R., and E. J. Snell.  1981.  Applied statistics: principles and examples.  Chapman and Hall, London, U.K.  189pp.

74.  Crane, J. A.  1980.  Relative likelihood analysis versus significance tests.  Evaluation Review 4:824-842.

75.  Cronbach, L. J.  1975.  Beyond the two disciplines of scientific psychology.  American Psychologist 30:116-127.

76.  Cutler, S. J., S. W. Greenhouse, J. Cornfield, and M. A. Schneiderman.  1966.  The role of hypothesis testing in clinical trials.  Journal of Chronic Diseases 19:857-882.

77.  Daniel, L. G.  1998.  Statistical significance testing: a historical overview of misuse and misinterpretation with implications for the editorial policies of educational journals.  Research in the Schools 5(2):23-32.

78.  Daniel, W. W.  1977.  Statistical significance versus practical significance.  Science Education 61:423-427.

79.  Dar, R.  1987.  Another look at Meehl, Lakatos, and the scientific practices of psychologists.  American Psychologist 42:145-151.

80.  Dar, R., R. C. Serlin, and H. Omer.  1994.  Misuse of statistical tests in three decades of psychotherapy research. Journal of Consulting and Clinical Psychology 62:75-82.

81.  DeGroot, M. H.  1989.  Probability and statistics.  Addison-Wesley, Reading, Mass.

82.  DeLong, J. B., and K. Lang.  1992.  Are all economic hypotheses false?  Journal of Political Economy 100:1257-1272.

83.  Deming, W. E.  1975.  On probability as a basis for action.  American Statistician 29:146-152.

84.  Diamond, G., and J. Forrester.  1983.  Clinical trials and statistical verdicts: probable grounds for appeal.  Annals of Internal Medicine 98:385-394.

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86.  Dixon, P., and T. O’Reilly.  1999.  Scientific versus statistical significance.  Canadian Journal of Experimental Psychology 53:133-149.

87.  Donders, J.  2000.  From null hypothesis to clinical significance.  Journal of Clinical and Experimental Neuropsychology 22:265-266.

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93.  Ellison, A. M.  1996.  An introduction to Bayesian inference for ecological research and environmental decision-making. Ecological Applications 6:1036-1046.

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96.  Falk, R.  1998.  In criticism of the null hypothesis statistical test.  American Psychologist 53:798-799.

97.  Falk, R., and C. W. Greenbaum.  1995.  Significance tests die hard: the amazing persistence of a probabilistic misconception. Theory and Psychology 5:75-98.

98.  Favreau, O. E.  1993.  Do the Ns justify the means?  Null hypothesis testing applied to sex and other differences.  Canadian Psychology 34:64-78.

99.  Favreau, O. E.  1997.  Sex and gender comparisons: Does null hypothesis testing create a false dichotomy?  Feminism and Psychology 7:63-81.

100.  Feinstein, A. R.  1977.  Clinical biostatistics.  C. V. Mosby, St. Louis, Mo.

101.  Feinstein, A. R.  1978.  Clinical biostatistics: stochastic significance, apposite data, and some remedies for the intellectual pollutants of statistical vocabulary.  Clinical Pharmaceutical Therapy 22:113-123.

102.  Feinstein, A. R.  1985.  Clinical epidemiology: the architecture of clinical research.  W. B. Saunders Co., Philadelphia, Penn.  812pp.

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104.  Finney, D. J.  1988.  Was this in your statistics textbook? III. Design and analysis.  Experimental Agriculture 24:421-432.

105.  Finney, D. J.  1989a.  Was this in your statistics textbook? VI.  Regression and covariance.  Experimental Agriculture 25:291-311.

106.  Finney, D. J.  1989b.  Is the statistician still necessary?  Biom. Praxim. 29:135-146.

107.  Folger, R.  1989.  Significance tests and the duplicity of binary decisions.  Psychological Bulletin 106:155-160.

108.  Freedman, D., R. Pisani, and R. Purves.  1978.  Statistics.  Norton Publ. Co., New York, N.Y.

109.  Freeman, P. R.  1993.  The role of p-values in analysing trial results.  Statistics in Medicine 12:1443-1452.

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112.  Gardner, M. J., and D. G. Altman.  1986.  Confidence intervals rather than P values: estimation rather than hypothesis testing.  British Medical Journal 292:746-750.

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118.  Gigerenzer, G.  1991.  From tools to theories: a heuristic of discovery in cognitive psychology.  Psychological Review 98:254-267.

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360.  Taylor, S., and S. Muncer.  2000.  Redressing the power and effect of significance.  A new approach to an old problem: teaching statistics to nursing students.  Nurse Education Today 20:358-364.

361.  Thompson, B.  1993.  The use of statistical significance tests in research: bootstrap and other alternatives.  Journal of Experimental Education 61:361-377.

362.  Thompson, B.  1996.  AERA editorial policies regarding statistical significance testing: three suggested reforms.  Educational Researcher 25:26-30.

363.  Thompson, B.  1997a.  Editorial policies regarding statistical significance tests: further comments.  Educational Researcher 26(5):29-32.

364.  Thompson, B.  1997b.  Statistical significance testing practices in The Journal of Experimental Education. Journal of Experimental Education 66:75-83.

365.  Thompson, B.  1998.  Statistical significance and effect size reporting: portrait of a possible future.  Research in the Schools 5(2):33-38.

366.  Thompson, B.  1999a.  Improving research clarity and usefulness with effect size indices as supplements to statistical significance tests.  Exceptional Children 65:329-337.

367.  Thompson, B. 1999b.  Journal editorial policies regarding statistical significance tests: heat is to fire as p is to importance. Educational Psychology Review 11:157-169.

368.  Thompson, B.  1999c.  If statistical significance tests are broken/misused, what practices should supplement or replace them? Theory and Psychology 9:167-183.

369.  Thompson, B.  1999d.  Statistical significance tests, effect size reporting, and the vain pursuit of pseudo-objectivity. Theory and Psychology 9:191-196.

370.  Thompson, B.  1999e.  Why “encouraging” effect size reporting is not working: the etiology of researcher resistance to changing practices.  Journal of Psychology 133:133-140.

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372.  Thompson, W. D.  1987.  Statistical criteria in the interpretation of epidemiologic data.  American Journal of Public Health 77:191-194.
 

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