InfluentialPoints.com
Biology, images, analysis, design...
Use/Abuse Stat.Book Beginners Stats & R
"It has long been an axiom of mine that the little things are infinitely the most important" (Sherlock Holmes)

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). http://dx.doi.org/10.1136/bmj.326.7387.475 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC150179/pdf/475.pdf [free]

 

Altman, D.G. & Bland, J.M. (1995). Statistics notes: Absence of evidence is not evidence of absence. BMJ 311, 485 (19 August). http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2550545/pdf/bmj00606-0027.pdf [free pdf]

 

Anderson, D.R. et al. (2000). Null hypothesis testing: problems, prevalence, and an alternative. Journal of Wildlife Management 64 (4), 912-923. http://dx.doi.org/10.2307/3803199 http://welcome.warnercnr.colostate.edu/~anderson/PDF_files/TESTING.pdf [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. http://assets.cambridge.org/97805218/09160/frontmatter/9780521809160_frontmatter.pdf

 

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. http://www.personal.kent.edu/~dfresco/CRM_Readings/Cohen_1990.pdf [free]

 

Cohen, J. (1994). The earth is round (p < 0.05). American Psychologist 49 (12), 997-1003. http://www.ics.uci.edu/~sternh/courses/210/cohen94_pval.pdf [free pdf]

 

Carver, R.P. (1978). The case against statistical significance testing. Harvard Educational Review 48 (3), 378-399. http://scholasticadministrator.typepad.com/thisweekineducation/files/the_case_against_statistical_significance_testing.pdf [free pdf]

 

Curran-Everett, D. (2009). Explorations in statistics: hypothesis tests and P values. Advances in Physiology Education 33, 81-86. http://dx.doi.org/10.1152/advan.90218.2008 http://advan.physiology.org/cgi/reprint/33/2/81.pdf [free pdf]

 

Denis, D.J. (2003). Alternatives to null hypothesis significance testing. Theory and Science 4 (1). http://theoryandscience.icaap.org/content/vol4.1/02_denis.html [free html]

 

Fidler, F. et al. (2004). Statistical reform in medicine, psychology and ecology. Journal of Socio-Economics 33, (5) 615-630. http://dx.doi.org/10.1016/j.socec.2004.09.035

 

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 http://www.faculty.biol.ttu.edu/Strauss/Stats/Readings/FidlerBurgmanCummingButtroseThomason2006.pdf [free pdf]

 

Gerrodette, T. (1987). A power analysis for detecting trends. Ecology 68 (5), 1364-1372. http://dx.doi.org/10.2307/1939220 http://people.stat.sfu.ca/~cschwarz/Stat-650/Notes/Handouts.readings/GerrodetteEcology1987.pdf [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. http://www.cchil.org/cru/Images/education/635842a09581fdb73c23c4f3e64c82ec.html [free html]

 

Goodman, S.N. & Royall, R. (1980). Evidence and scientific research. American Journal of Public Health 78 (12), 1568-1574. http://www.pubmedcentral.nih.gov/picrender.fcgi?artid=1349737&blobtype=pdf [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. http://dx.doi.org/10.2307/3803089

 

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. http://dx.doi.org/10.1046/j.1523-1739.1997.96034.x

 

Hobbs, N.T. & Hilborn, R. (2006). Alternatives to statistical hypothesis testing in ecology: a guide to self teaching. Ecological Applications 16 (1), 5-19. http://dx.doi.org/10.1890/04-0645 http://www.sortie-nd.org/lme/Statistical%20Papers/Hobbs_and_Hilborn_Ecol_Appl_2006.pdf [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. http://www.ingentaconnect.com/content/asa/tas/2001/00000055/00000001/art00004 http://www.fisheries.vims.edu/hoenig/pdfs/hoenig2.pdf [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. http://www.bio.sdsu.edu/pub/stuart/2009FinalCollapseX.pdf [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. http://beheco.oxfordjournals.org/cgi/reprint/14/3/438.pdf [free pdf]

 

Johnson, D.H. (1999). The insignificance of statistical significance testing. Journal of Wildlife Management 63 (3), 763-772. http://dx.doi.org/10.2307/3802789 http://www.npwrc.usgs.gov/resource/methods/statsig/index.htm [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. http://www.sortie-nd.org/lme/Likelihood%20Applications%20in%20Ecology/Loehle_QRB_1987.pdf [free pdf]

 

Lombardi, C.M. & Hurlbert, S.H. (2009). Misprescription and misuse of one-tailed tests. Austral Ecology 34, 447-468. http://dx.doi.org/10.1111/j.1442-9993.2009.01946.x http://www.bio.sdsu.edu/pub/stuart/2009MisprescriptionOneTailed.pdf [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. http://www.jstor.org/stable/2685470 http://www.uvm.edu/~rsingle/stat380/F04/papers/Ludbrook+Dudley-AmStat1998_PermTests.pdf [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. http://dx.doi.org/10.1111/j.1365-2664.2006.01267.x http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2664.2006.01267.x/pdf [free pdf]

 

McPherson, G. (1989). The scientists' view of statistics - a neglected area. Journal of the Royal Statistical Society 152 (2), 221-240. http://dx.doi.org/10.2307/2982916

 

Moore, G.E. (1903). Principia Ethica. Prometheus Books. (Preface) http://fair-use.org/g-e-moore/principia-ethica/ [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. http://dx.doi.org/10.1111/j.1469-185X.2007.00027.x http://www.bio.bris.ac.uk/research/behavior/R_scripts/Nakagawa%20Cuthill%20BR%202007.pdf [free pdf]

 

Nester, M.R. (1996). An applied statistician's creed. Applied Statistics 45 (4), 401-410. http://dx.doi.org/10.2307/2986064

 

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. http://dx.doi.org/10.1002/sim.1296 http://psg-mac43.ucsf.edu/ticr/syllabus/courses/26/2003/01/16/lecture/readings/pocock.pdf [free pdf]

 

Poole, C. (1987). Beyond the confidence interval. American Journal of Public Heath 77 (2), 195-199. http://www.pubmedcentral.nih.gov/picrender.fcgi?artid=1646825&blobtype=pdf [free pdf]

 

Reese, R.A. (2004). Does significance matter? Significance, 1 (1), 39-40. http://dx.doi.org/10.1111/j.1740-9713.2004.00009.x

 

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. http://dx.doi.org/10.1016/0169-5347(94)90258-5

 

Robinson, D.H. & Wainer, H. (2002). On the past and future of null hypothesis significance testing. Journal of Wildlife Management 66 (2), 263-271. http://dx.doi.org/10.2307/3803158 http://www.ets.org/Media/Research/pdf/RR-01-24-Wainer.pdf [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. http://www.stats.org.uk/statistical-inference/Rozeboom1960.pdf [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. http://dx.doi.org/10.1111/j.2041-210X.2010.00014.x

 

Shaw, G.B. (1921). Back to Methuselah, pt. I, act I. http://www.gutenberg.org/files/13084/13084-8.txt [free text]

 

Steidl, R.J. et al. (1997). Statistical power analysis in wildlife research. Journal of Wildlife Management 61 (2), 270-279. http://people.stat.sfu.ca/~cschwarz/Stat-650/Notes/Handouts.readings/Steidl1997JWM.pdf [free pdf]

 

Di Stefano, J. (2004). A confidence interval approach to data analysis. Forest Ecology and Management 187 (2-3), 173-183. http://dx.doi.org/10.1016/S0378-1127(03)00331-1

 

Schulz, K.F. & Grimes, D.A. (2005). Sample size calculations in randomised trials: mandatory and mystical. Lancet 365, 1348-1353 (9-15 April). http://dx.doi.org/10.1016/S0140-6736(05)61034-3 http://download.thelancet.com/pdfs/journals/0140-6736/PIIS0140673605610343.pdf

 

Stoehr, A.M. (1999). Are significance thresholds appropriate for the study of animal behaviour? Animal Behaviour 57 (5), 22-25. http://dx.doi.org/10.1006/anbe.1998.1016

 

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. http://dx.doi.org/10.1111/j.1365-2664.2005.01002.x http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2664.2005.01002.x/pdf [free pdf]

 

Stephens, P.A. et al. (2007). A call for statistical pluralism answered. Journal of Applied Ecology 44 (2), 461-463 http://dx.doi.org/10.1111/j.1365-2664.2007.01302.x http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2664.2007.01302.x/pdf [free pdf]

 

Stephens, P.A. et al. (2007) . Inference in ecology and evolution. TRENDS in Ecology and Evolution 22 (4), 4-12. http://dx.doi.org/10.1016/j.tree.2006.12.003 http://ww2.tnstate.edu/biology/chalktalk/2008%20files/Phil%20Ganter/Stephens%202007%20TREE.pdf [free pdf]

 

Sterne, J.A. (2002). Teaching hypothesis tests - time for significant change. Statistics in Medicine 21, 985-994. http://dx.doi.org/10.1002/sim.1129

 

Sterne, J. (2003). Commentary: Null points - has interpretation of significance tests improved? International Journal of Epidemiology 32, (5) 693-694. http://dx.doi.org/10.1093/ije/dyg274 http://ije.oxfordjournals.org/cgi/reprint/32/5/693.pdf [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. http://www.creem.st-and.ac.uk/len/papers/ThomasBESA1997.pdf [free pdf]

 

Thomas, L. (1997). Retrospective power analysis. Conservation Biology 11 (1), 276-280. http://dx.doi.org/10.1046/j.1523-1739.1997.96102.x

 

Weinberg, C.R. (2001). It's time to rehabilitate the P_value. Epidemiology 12 (3), 288-290. http://www.epidem.com/pt/re/epidemiology/pdfhandler.00001648-200105000-00004.pdf [free html]

 

Wittes, J. (2002). Sample size calculations for randomized controlled trials. Epidemiologic Reviews 24 (1), 39-53. http://epirev.oxfordjournals.org/cgi/reprint/24/1/39.pdf [free pdf]

 

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