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Statistics bibliography 05 - stats

Alderson, P. & Chalmers, I. (2003). Survey of claims of no effect in abstracts of Cochrane reviews. BMJ 326, 475 (1 March). [free]


Altman, D.G. & Bland, J.M. (1995). Statistics notes: Absence of evidence is not evidence of absence. BMJ 311, 485 (19 August). [free pdf]


Anderson, D.R. et al. (2000). Null hypothesis testing: problems, prevalence, and an alternative. Journal of Wildlife Management 64 (4), 912-923. [free pdf]


Bausell, R.B. & Li, Y.F. (2002). Power analysis for experimental research: A practical guide for the biological, medical and social sciences. Cambridge University Press. 376 pp.


Cohen, J. (1988). Statistical power analysis for the behavioral sciences. 2nd Edn. Lawrence Erlbaum, Hillsdale, New Jersey. 567 pp.


Cohen, J. (1990). Things I have learned so far. American Psychologist 45 (12), 1304-1312. [free]


Cohen, J. (1994). The earth is round (p < 0.05). American Psychologist 49 (12), 997-1003. [free pdf]


Carver, R.P. (1978). The case against statistical significance testing. Harvard Educational Review 48 (3), 378-399. [free pdf]


Curran-Everett, D. (2009). Explorations in statistics: hypothesis tests and P values. Advances in Physiology Education 33, 81-86. [free pdf]


Denis, D.J. (2003). Alternatives to null hypothesis significance testing. Theory and Science 4 (1). [free html]


Fidler, F. et al. (2004). Statistical reform in medicine, psychology and ecology. Journal of Socio-Economics 33, (5) 615-630.


Fidler, F. et al. (2006). Impact of criticisms of null-hypothesis significance testing on statistical reporting practices in conservation biology. Conservation Biology 20, (5) 1539-1544. 10.1111/j.1523-1739.2006.00525.x [free pdf]


Gerrodette, T. (1987). A power analysis for detecting trends. Ecology 68 (5), 1364-1372. [free pdf]


Goodman, S.N. & Berlin, J.A. (1994). The use of predicted confidence intervals when planning experiments and the misuse of power when interpreting results. Annals of Internal Medicine 121 (3), 200-206. [free html]


Goodman, S.N. & Royall, R. (1980). Evidence and scientific research. American Journal of Public Health 78 (12), 1568-1574. [free pdf]


Griffiths, D. et al. (1998). Understanding Data. Principles and Practice of Statistics. Wiley, Brisbane.


Guthery, F.S. et al. (2001). The fall of the null hypothesis: Liabilities and opportunities. Journal of Wildlife Management 65 (3), 379-384.


Harlow, L.L. et al. (1997). What if there were no significance tests? Lawrence Erlbaum, Mahwah, NJ. 454 pp. [not available in full on line]


Jeffreys, H. (1961). Theory of probability. 3rd Edn. Oxford University Press, Oxford. [not available online]


Hayes, J.P. & Steidl, R.J. (1997). Statistical power analysis and amphibian population trends. Conservation Biology 11 (1), 273-275.


Hobbs, N.T. & Hilborn, R. (2006). Alternatives to statistical hypothesis testing in ecology: a guide to self teaching. Ecological Applications 16 (1), 5-19. [free pdf]


Hoenig, J.M. & Heisey, D.M. (2001). The abuse of power: the pervasive fallacy of power calculations for data analysis. American Statistician 55 (1), 19-24. [free pdf]


Hurlbert, S.H. & Lombardi, C.M. (2009). Final collapse of the Neyman-Pearson decision theoretic framework and rise of the neo-Fisherian. Annales Zoologica Fennici. 46, 311-349. [free pdf]


Jennions, M.D. & Moller, A.P. (2003). A survey of the statistical power of research in behavioral ecology and animal behavior. Behavioral Ecology 14, (3) 438-445. [free pdf]


Johnson, D.H. (1999). The insignificance of statistical significance testing. Journal of Wildlife Management 63 (3), 763-772. [free html]


Kline, R.B. (2004). Beyond significance testing: Reforming data analysis methods in behavioral research. APA Books. 325 pp. [not available in full on line]


Loehle, C. (1987). Hypothesis testing in ecology: Psychological aspects and the importance of theory maturation. The Quarterly Review of biology 62 (4), 397-409. [free pdf]


Lombardi, C.M. & Hurlbert, S.H. (2009). Misprescription and misuse of one-tailed tests. Austral Ecology 34, 447-468. [free pdf]


Ludbrook, J. & Dudley, H. (1998). Why permutation tests are superior to t and F tests in biomedical research. The American Statistician 52 (2), 127-132. [free pdf]


Lukacs et al. (2007). Concerns regarding a call for pluralism of information theory and hypothesis testing. Journal of Applied Ecology 44 (2), 456-460. [free pdf]


McPherson, G. (1989). The scientists' view of statistics - a neglected area. Journal of the Royal Statistical Society 152 (2), 221-240.


Moore, G.E. (1903). Principia Ethica. Prometheus Books. (Preface) [free html]


Murphy, K.R. & Myors, B. (2003). Statistical power analysis: A simple and general model for traditional and modern hypothesis tests 2nd Edn. Taylor & Francis. 128 pp. [not available in full on line]


Nakagawa, S. & Cuthill, I.C. (2007). Effect size, confidence interval and statistical significance: a practical guide for biologists. Biological Reviews 82 (4), 591-605. [free pdf]


Nester, M.R. (1996). An applied statistician's creed. Applied Statistics 45 (4), 401-410.


Pocock, S.J. et al. (2002). Subgroup analysis, covariate adjustment and baseline comparisons in clinical trial reporting: current practice and problems. Statistics in Medicine 21 (19), 2917-2930. [free pdf]


Poole, C. (1987). Beyond the confidence interval. American Journal of Public Heath 77 (2), 195-199. [free pdf]


Reese, R.A. (2004). Does significance matter? Significance, 1 (1), 39-40.


Rice, W.R. & Gaines, S.D. (1994). 'Heads I win, tails you lose': testing directional alternative hypotheses in ecological and evolutionary research. Trends in Ecology & Evolution 9 (6), 235-237.


Robinson, D.H. & Wainer, H. (2002). On the past and future of null hypothesis significance testing. Journal of Wildlife Management 66 (2), 263-271. [free pdf]


Rothman, K.J. and Greenland, S. (1998). Modern Epidemiology. 2nd Edn. Lippincott-Raven, Philadelphia.


Rozeboom, W.W. (1960). The fallacy of the null hypothesis significance test. Psychological Bulletin 57 (5), 416-428. [free pdf]


Ruxton, G.D. & Neuhuser, M. (2010). When should we use one-tailed hypothesis testing? Methods in Ecology and Evolution 1 (2), 114-117.


Shaw, G.B. (1921). Back to Methuselah, pt. I, act I. [free text]


Steidl, R.J. et al. (1997). Statistical power analysis in wildlife research. Journal of Wildlife Management 61 (2), 270-279. [free pdf]


Di Stefano, J. (2004). A confidence interval approach to data analysis. Forest Ecology and Management 187 (2-3), 173-183.


Schulz, K.F. & Grimes, D.A. (2005). Sample size calculations in randomised trials: mandatory and mystical. Lancet 365, 1348-1353 (9-15 April).


Stoehr, A.M. (1999). Are significance thresholds appropriate for the study of animal behaviour? Animal Behaviour 57 (5), 22-25.


Sokal, R.R. & Rohlf, F.J. (1995). Biometry. The principles and practice of statistics in biological research. 3rd Edn. Freeman, New York.


Stephens, P.A. et al. (2005) . Information theory and hypothesis testing: a call for pluralism. Journal of Applied Ecology 42, 4-12. [free pdf]


Stephens, P.A. et al. (2007). A call for statistical pluralism answered. Journal of Applied Ecology 44 (2), 461-463 [free pdf]


Stephens, P.A. et al. (2007) . Inference in ecology and evolution. TRENDS in Ecology and Evolution 22 (4), 4-12. [free pdf]


Sterne, J.A. (2002). Teaching hypothesis tests - time for significant change. Statistics in Medicine 21, 985-994.


Sterne, J. (2003). Commentary: Null points - has interpretation of significance tests improved? International Journal of Epidemiology 32, (5) 693-694. [free pdf]


Thomas, L. & Krebs, C.J. (1997). A review of statistical power analysis software. Bulletin of the Ecological Society of America 78 (2), 128-139. [free pdf]


Thomas, L. (1997). Retrospective power analysis. Conservation Biology 11 (1), 276-280.


Weinberg, C.R. (2001). It's time to rehabilitate the P_value. Epidemiology 12 (3), 288-290. [free html]


Wittes, J. (2002). Sample size calculations for randomized controlled trials. Epidemiologic Reviews 24 (1), 39-53. [free pdf]


Zar, J.H. (1999). Biostatistical analysis. 4th Edn. Prentice Hall International, London.