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Statistics bibliography 08 - stats

Armitage, P. & Berry, G. (2002). Statistical methods in medical research. 4th Edn. Blackwells, Oxford.


Arthur, S.M. et al. (1996). Assessing habitat selection when availability changes. Ecology 77 (1), 215-227


Behrens, W.U. (1929). Ein Betrag zur Felerberechnung bei weinigen Beobachtungen. Lanwirtschaftliche Jahrbucher 68, 807-837.


Bennett, S. et al. (2002). Methods for the analysis of incidence rates in cluster randomized trials. International Journal of Epidemiology 31 (4), 839-846. [free pdf]


Bland, J.M. & Kerry, S.M. (1998). Weighted comparison of means. BMJ 316, 129 (10 January). [free pdf]


Box, J.F. (1987). Guinness, Gosset, Fisher, and Small Samples. Statistical Science 2 (1), 45-52. [free pdf]


Conover, W.J. et al. (1992). A comparative study of tests for homogeneity of variances, with applications to the outer continental shelf bidding data. Technometrics 23 (4), 351-361.


Diaz-Uriarte, R. (2002). Incorrect analysis of crossover trials in animal behaviour research. Animal Behaviour 63, 815-822. [free pdf]


Donner, A. & Donald, A. (1982). Analysis of data arising from a stratified design with the cluster as unit of randomization. Journal of the Royal Statistical Society. Series C (Applied Statistics) 31 (1), 9-13.


Everitt, B.S. (1998). Cambridge Dictionary of Statistics. Cambridge University Press, Cambridge, UK.


Donner, A. (1987). Statistical methodology for paired cluster designs. American Journal of Epidemiology 126 (5), 972-979.


Diehr, P. et al. 1995. Breaking the matches in a paired t-test for community interventions when the number of pairs is small. Statistics in Medicine 14, 1491-1504. [free pdf]


Donner, A. (1993).The comparison of proportions in the presence of litter effects. Preventive Veterinary Medicine, 18, 17-26.


Donner, A. & Klar, N. (1994). Methods for comparing event rates in intervention studies when the unit of allocation is a cluster. American Journal of Epidemiology 140 (3), 279-289.


Albert Einstein (1950). Out of my later years. Philosophical Library, New York.


Fisher, R.A. (1941). The asymptotic approach to Behren's integral, with further tables for the d test of significance. Annals of Eugenics, London 10, 48-51. [free pdf]


Gans (1991). Preliminary test on variances. American Statistician 45, 258.


Horton, D.R. (1995). Statistical considerations in the design and analysis of paired-choice assays. Environmental Entomology 24 (2), 179-192.


Hurlbert, S.H. (1984) Pseudoreplication and the design of ecological field experiments. Ecological Monographs 54 (2), 187-211. [free pdf]


Johnson, D.H. (1995). Statistical sirens - the allure of nonparametrics. Ecology 76 (6), 1998-2000. [free pdf]


Klar, N. & Donner, A. (1997). The merits of matching in community intervention trials: a cautionary tale. Statistics in Medicine 16 (15), 1753-1764.<1753::AID-SIM597>3.0.CO;2-E


Kerry, S.M. & Bland, J.M. (1998). Statistics notes. Analysis of a trial randomised in clusters. BMJ 316, 54 (3 January). [free pdf]


Manly, B.F.J. (1997). Randomization, bootstrap, and Monte Carlo methods in biology. 2nd Edn. Chapman & Hall, London.


Markowski, C.A. & Markowski, E.P. (1990). Conditions for the effectiveness of a preliminary test of variance. The American Statistician 44 (4): 322-326.


Menke, J. & Martinez, T.R. (2004). Using permutations instead of Student's t distribution for p-values in paired-difference algorithm comparisons. Neural Networks, 2004. Proceedings of IEEE International Joint Conference 25-29 July 2004. Vol 2, 1331- 1335 . [free pdf]


Moser, B.K. & Stevens, G.R. (1992). Homogeneity of variance in the two-sample means test. The American Statistician 46 (1), 19-21.


Noreen, E.W. (1989). Computer intensive methods for testing hypotheses, an introduction. John Wiley & Sons Inc, New York.


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


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


Potvin, C. & Roff, D.A. (1993). Distribution-free and robust statistical methods: Viable alternatives to parametric statistics? Ecology 74 (6), 1617-1628. [free pdf]


Smith, S. (1995). Distribution-free and robust statistical methods: viable alternatives to parametric statistics. Ecology 76 (6), 1997-1998. [free pdf]


Snedecor, G.W. & Cochran, W.G. (1989). Statistical Methods. 8th Edn. Iowa State Press, Iowa, USA.


Tu, Y.-K. et al. (2008). Simpson's Paradox, Lord's Paradox, and Suppression Effects are the same phenomenon - the reversal paradox. Emerging Themes in Epidemiology 5: 2 [free pdf]


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


Wainer, H. (1991). Adjusting for differential base rates: Lord's paradox again. Psychological Bulletin 109 (1), 147-151. [free pdf]


Woodward, M. (2004). Epidemiology. Study Design and Analysis. 2nd edn. Chapman & Hall/CRC, Boca Raton. 872 pp.


Welch, B.L. (1947). The generalization of 'Student's' problem when several populations are involved. Biometrika 34 (1-2), 28-35.


Wright, D.B.I. (2006). Comparing groups in a before-after design: When t test and ANCOVA produce different results. British Journal of Educational Psychology 76 (3), 663-675.


Yudkin, P.L. & Moher, M. (2001). Putting theory into practice: a cluster randomized trial with a small number of clusters. Statistics in Medicine 20 (3), 341-349.<341::AID-SIM796>3.0.CO;2-G


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


Zimmerman, D.W. (1997). A note on interpretation of the paired-samples t test. Journal of Educational and Behavioral Statistics 22 (3), 349-360.


Zimmerman, D.W. (2004). Inflation of Type I error rates by unequal variances associated with parametric, nonparametric, and rank-transformation tests. Psicologica 25, 103-133. [free pdf]


Zimmerman, D.W. (2004). A note on preliminary tests of equality of variances. British Journal of Mathematical and Statistical Psychology 25, 103-133.


Zimmerman, D.W. (2004). Inflated statistical significance of Student's t test associated with small intersubject correlation. Journal of Statistical Computation and Simulation 74, 691-696.


Zimmerman, D.W. (2005). Increasing power in paired-samples designs by correcting the Student t statistic for correlation. Interstat [free pdf]


Zimmerman, D.W. & Zumbo, B.D. (2009). Hazards in choosing between pooled and separate-variances t tests. Psicologica 30, 371-390. [free pdf]