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Statistics bibliography 11 - stats

Altman, D.G. & Bland, J.M. (1996). Statistics Notes: Comparing several groups using analysis of variance. BMJ 312, 1472-1473 (8 June). [free]


Adams, D. & Carwardine, M. (1991). Last chance to see.... Pan Books, London.


Anonymous (2007). Dr Fisher's casebook. Significance 4 (1), 26.


Bland, J.M. & Altman, D.G. (1995). Statistics notes. Multiple significance tests: the Bonferroni method. BMJ 310, 170 (21 January). [free pdf]


Benjamini, Y. & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society B, 57, 289-300. [free pdf]


Bewick, V. et al. (2004). Statistics review 9: One-way analysis of variance. Critical Care 8 (2), 130-136. [free pdf]


Bland, J.M. & Altman, D.G (1996). Measurement error and correlation coefficients. BMJ 313, 41-42 (6 July). [free html]


Brown, M.B. & Forsythe, A.N. (1974). Robust tests for the equality of variances. Journal of the American Statistical Association 69 (346), 364-367.


Conover, W.J. (1999). Practical nonparametric statistics. 3rd Edn. John Wiley & Sons, New York.


Day, R.W. & Quinn, G.P. (1989). Comparisons of treatments after an analysis of variance in ecology. Ecological Monographs 59 (4), 433-463. [free pdf]


Doncaster, C.P. & Davey, A.J.H. (2007). Analysis of variance and covariance: How to choose and construct models for the life sciences. Cambridge University Press, Cambridge. 302pp.


Dunnett, C.W. (1955). A multiple comparisons procedure for comparing several treatments with a control. Journal of the American Statistical Association 50, 1096-1121.


Dunn, O.J. (1964). Multiple comparisons using rank sums, Technometrics 6 (3), 241-252.


Einot, I. & Gabriel, K.R. (1985). A study of the powers of several methods of multiple comparisons. Journal of the American Statistical Association 70 (351), 574-583. [free pdf]


Feise, R.J. (2002). Do multiple outcome measures require p-value adjustment. BMC Medical Research Methodology 2:8 [free pdf]


Fligner, M.A. & Policello, G.E. (1981). Robust rank procedures for the Behrens-Fisher problem. Journal of the American Statistical Association 76 (373), 162-168.


Fisher, R.A. (1935). The design of experiments. 1st Edition. Oliver & Boyd, Edinburgh, Scotland.


Garcia, L.V. (2004) Escaping the Bonferroni iron claw in ecological studies. Oikos 105 (3), 657-663.


Gill, J.L. (1990). Uses and abuses of statistical methods in research in parasitology. Veterinary Parasitology 36 (3-4), 189-209. [abstract only]


Gill, J.L. (1978). Design and analysis of experiments in the animal and medical sciences. Vol 3. Appendices. The Iowa State University Press Ames, IA.


Hollander, M. & Wolfe, D.A. (1973). Nonparametric statistical methods. Wiley & Sons, New York.


Keselman, H.J. et al. (1998). Statistical practices of educational researchers: An analysis of their ANOVA, MANOVA and ANCOVA analyses. Review of Educational Research 68 (3), 350-386.


Keuls, M. (1952). The use of the "studentized range" in connection with the analysis of variance. Euphytica 1 (2), 112-122.


Kruskal, W. (1980). The significance of Fisher: a review of 'R. A. Fisher: The Life of a Scientist' by J.F. Box. Journal of the American Statistical Association 75 (372), 1019-1030.


Kruskal, W.H. & Wallis, W.A. (1952). Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association 47 (260), 583-621. [abstract only]


Kerry, S.M. & Bland, J.M. (1998). Statistics notes. The intracluster correlation coefficient in cluster randomisation. BMJ 316, 1455-1460 (9 May). [free pdf]


Lowry, S.R. (1992). Use and misuse of multiple comparisons in animal experiments. Journal of Animal Science 70, 1971-1977. [free pdf]


McGraw, K.O. & Wong, S.P. (1996). Forming inferences about some intraclass correlation coefficients. Psychological Methods 1 (1), 30-46.


Moran, M.D. (2003). Arguments for rejecting the sequential Bonferroni in ecological studies. Oikos 100 (2), 403-405. [free pdf]


Müller & Büttner (1994) A critical discussion of intraclass correlation coefficients. Statistics in Medicine, 13 (23-24), 2465-2476.


Nelder, J.A. (1971). Contribution to the discussion of O'Neil, R.T. & Wetherill, B.G. (1971). The present state of multiple comparison methods. Journal of the Royal Statistical Society B 33, 241-250


Newman, D. (1939). The distribution in range of samples from a normal population, expresssed in terms of an independent estimate of standard deviation. Biometrika 31 (1-2), 20-30.


Nemenyi, P. (1963). Distribution-free multiple comparisons. Dissertation. Princeton University, Princeton, New Jersey.


Neuhauser, M. (2002). Two sample tests when variances are unequal. Animal Behaviour 63 (4), 823-825.


Pagel, M.D. (1992). A method for the analysis of comparative data. Journal of Theoretical Biology 156 (4), 431-442.


Perry, J.N. (1986). Multiple-comparison procedures: A dissenting view. Journal of Economic Entomology 79 (5), 1149-1155.


Perneger, T.V. (1998). What's wrong with Bonferroni adjustments? BMJ 316, 1236-1238 (18 April). [free html]


Rice, W.R. (1989). Analyzing tables of statistical tests. Evolution 43, 223-225. 1500%20readings/Bonferroni/rice%2089%20seq%20bonferroni%20test.pdf [free pdf]


Rothman, K.J. (1990). No adjustments are needed for multiple comparisons. Epidemiology 1 (1), 43-46. [abstract only]


Steel, R.G.D. (1959). A multiple comparison rank sum test: treatment versus control. Biometrics 15, 560-572.


Siegel, S. & Castellan, N.J. Jr. (1988) . Nonparametric statistics for the behavioral sciences. 2nd Edn. McGraw-Hill, New York.


Steel, R.G.D. (1960). A rank sum test for comparing all treatments. Technometrics 2, 197-207.


Shrout, P.E. & Fleiss, J.L. (1979). Intraclass correlations: Uses in assessing rater reliability. Psychological Bulletin 86 (2), 420-428. [free pdf]


Siegel, S. (1956). Nonparametric Statistics for the Behavioural Sciences. McGraw-Hill Kogakusha, Tokyo.


Steel, R.G.D. (1961). Some rank sum multiple comparison tests. Biometrics 17, 539-552.


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


Sprent, P. (1998). Data driven statistical methods. Chapman & Hall, London.


Steel, R.G.D. & Torrie, J.H. (1960). Principles and procedures of statistics with special reference to the biologial sciences. McGraw Hill, New York.


Stewart-Oaten, A. (1995). Rules and judgements in statistics: three examples. Ecology 76 (6), 2001-2009.


Henri Theil (1971). Principles of econometrics. Wiley, New York.


Tukey, J.W. (1953). Some selected quick and easy methods of statistical analysis. Transactions of the New York Academy of Sciences, Series 2 16, 88-97.


Underwood, A.J. (1997). Experiments in ecology: Their logical design and interpretation using analysis of variance. Cambridge University Press. Cambridge, UK


Ury, H.K. (1976). A comparison of four procedures for multiple comparisons among means - pairwise contrasts for arbitrary sample sizes. Technometrics 18, 89-97.


Wallenstein, S. et al.. (1980). Some statistical methods useful in circulation research. Circulation Research 47, 1-9. [free pdf]


Wilcox, R.R. (1995). ANOVA: A paradigm for low power and misleading measures of effect size? Review of Educational Research 65 (1), 51-77.


Welch, B.L. (1951) On the comparison of several mean values: an alternative approach. Biometrika, 38 (3-4), 330-336.


Wilson, J.B. (2007). Priorities in statistics, the sensitive feet of elephants, and don't transform data. Folia Geobotanica 42 (2), 161-167. the_sensitive_feet_of_elephants_and_dont_transform_data_104.pdf [free pdf]


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