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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 http://dx.doi.org/10.2307/2265671

 

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. http://ije.oxfordjournals.org/cgi/reprint/31/4/839.pdf [free pdf]

 

Bland, J.M. & Kerry, S.M. (1998). Weighted comparison of means. BMJ 316, 129 (10 January). http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2665397/pdf/9462320.pdf [free pdf]

 

Box, J.F. (1987). Guinness, Gosset, Fisher, and Small Samples. Statistical Science 2 (1), 45-52. http://www.jstor.org/stable/2245613 http://projecteuclid.org/DPubS/Repository/1.0/Disseminate?view=body&id=pdf_1&handle=euclid.ss/1177013437 [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. http://dx.doi.org/10.1080/00401706.1981.10487680

 

Diaz-Uriarte, R. (2002). Incorrect analysis of crossover trials in animal behaviour research. Animal Behaviour 63, 815-822. http://dx.doi.org/10.1006/anbe.2001.1950 http://ligarto.org/rdiaz/Papers/cross-over-animal-behaviour.pdf [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. http://dx.doi.org/10.1002/sim.4780060106

 

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. http://aje.oxfordjournals.org/cgi/content/abstract/126/5/972

 

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. http://works.bepress.com/cgi/viewcontent.cgi?article=1017&context=paula_diehr [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. http://aje.oxfordjournals.org/cgi/content/abstract/140/3/279

 

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. http://hdl.handle.net/2440/15241 [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. http://www.ingentaconnect.com/content/esa/envent/1995/00000024/00000002/art00002

 

Hurlbert, S.H. (1984) Pseudoreplication and the design of ecological field experiments. Ecological Monographs 54 (2), 187-211. http://dx.doi.org/10.2307/1942661 http://www.bio.sdsu.edu/pub/stuart/1984Pseudoreplication.pdf [free pdf]

 

Johnson, D.H. (1995). Statistical sirens - the allure of nonparametrics. Ecology 76 (6), 1998-2000. http://dx.doi.org/10.2307/1940733 http://dx.doi.org/10.2307/1942661 http://botanika.bf.jcu.cz/suspa/mulvar/materialy/Johnson_NonParametrics.pdf [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. http://dx.doi.org/10.1002/(SICI)1097-0258(19970815)16:15<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). http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2665333/pdf/9451271.pdf [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. http://www.jstor.org/stable/2684360

 

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 . http://synapse.cs.byu.edu/papers/menke_2004_permutations.pdf [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. http://dx.doi.org/10.1080/00031305.1992.10475839

 

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. http://dx.doi.org/10.2307/2986064 http://www.sortie-nd.org/lme/Statistical%20Papers/Nester_1996.pdf [free pdf]

 

Neuhauser, M. (2002). Two sample tests when variances are unequal. Animal Behaviour 63 (4), 823-825. http://dx.doi.org/10.1006/anbe.2002.1993

 

Potvin, C. & Roff, D.A. (1993). Distribution-free and robust statistical methods: Viable alternatives to parametric statistics? Ecology 74 (6), 1617-1628. http://dx.doi.org/10.2307/1940734 http://botanika.bf.jcu.cz/suspa/mulvar/materialy/Potvin_Roff_NonParametrics.pdf [free pdf]

 

Smith, S. (1995). Distribution-free and robust statistical methods: viable alternatives to parametric statistics. Ecology 76 (6), 1997-1998. http://dx.doi.org/10.2307/1940732 http://www.tiehh.ttu.edu/scox/readings/Ecology76-1997-1998.pdf [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 http://dx.doi.org/10.1186/1742-7622-5-2 http://www.ete-online.com/content/pdf/1742-7622-5-2.pdf [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. http://dionysus.psych.wisc.edu/Lit/Articles/WainerH1991a.pdf [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. http://dx.doi.org/10.1093/biomet/34.1-2.28

 

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. http://dx.doi.org/10.1348/000709905X52210

 

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. http://dx.doi.org/10.1002/1097-0258(20010215)20:3<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. http://dx.doi.org/10.3102/10769986022003349

 

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. http://www.uv.es/psicologica/articulos1.04/6-zimmerman.pdf [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. http://dx.doi.org/10.1348/000711004849222

 

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. http://dx.doi.org/10.1080/00949650310001640129

 

Zimmerman, D.W. (2005). Increasing power in paired-samples designs by correcting the Student t statistic for correlation. Interstat http://interstat.statjournals.net/YEAR/2005/articles/0509002.pdf [free pdf]

 

Zimmerman, D.W. & Zumbo, B.D. (2009). Hazards in choosing between pooled and separate-variances t tests. Psicologica 30, 371-390. http://www.uv.es/revispsi/articulos2.09/12ZIMMERMAN.pdf [free pdf]