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Statistics bibliography 12 - stats

Altman, D.G. & Bland, J.M. (1983). Measurement in medicine: the analysis of method comparison studies. The Statistician 32, 307-317. http://dx.doi.org/10.2307/2987937 http://www-users.york.ac.uk/~mb55/meas/ab83.pdf [free pdf]

 

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

 

Brett, M.T. (2004). When is a correlation between non-independent variables "spurious"? Oikos 105 (3), 647-656. http://dx.doi.org/10.1111/j.0030-1299.2004.12777.x

 

Berges, J.A. (1997). Ratios, regression statistics, and "spurious" correlations. Limnology & Oceanography 42 (5), 1006-1007. http://www.aslo.org/lo/toc/vol_42/issue_5/1006.pdf [free pdf]

 

Bland, J.M. & Altman, D.G (1996). Measurement error and correlation coefficients. BMJ 313, 41-42 (6 July). http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2351452/pdf/bmj00549-0045.pdf [free html]

 

Batterham, A.M. ( 2004). Commentary on Bias in Bland-Altman but not Regression Validity Analyses Sportscience 8, 47-49. http://ww.sportsci.org/jour/04/amb.htm[free html]

 

Carroll, R.J. & Ruppert, D. (1996). The use and misuse of orthogonal regression estimation in linear errors-in-variables models. The American Statistician 50, 1-6. http://www.jstor.org/pss/2685035

 

Carroll, R.J. et al. (2006). Measurement error in nonlinear models: A modern perspective. Chapman & Hall / CRC Press.

 

Chalmer, B.J. & Whitmore, D.G. (1986). Understanding Statistics. CRC Press.

 

Chambers, J.M. et al. (1983). Graphical methods for data analysis. Wadsworth International Group/Duxbury Press, Belmont & Boston.

 

Clarke, M.R.B. (1980). The reduced major axis of a bivariate sample. Biometrika 67 (2), 441-446. http://dx.doi.org/10.1093/biomet/67.2.441

 

Cleveland, W.S. (1979). Robust locally weighted regression and smoothing scatterplots. Journal of the American Statistical Association 74, 829-836. http://www.aliquote.org/cours/2012_biomed/biblio/Cleveland1979.pdf [free pdf]

 

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

 

Cornbleet P.J. & Gochman N. (1979). Incorrect least-squares regression coefficients in method-comparison analysis. Clinical Chemistry 25 (3), 432-439. http://www.clinchem.org/cgi/reprint/25/3/432.pdf [free pdf]

 

Daniels, H.E. (1950). Rank correlation and population models. Journal of the Royal Statistical Society (B) 12, 171-181. http://www.jstor.org/stable/2983980

 

Fuller, W.A. (1987). Measurement error models. Wiley, New York.

 

Garcia-Berthou, E. (2001). On the misuse of residuals in ecology: testing regression residuals vs. the analysis of covariance. Journal of Animal Ecology 70 (4), 708-711. http://dx.doi.org/10.1046/j.1365-2656.2001.00524.x http://onlinelibrary.wiley.com/doi/10.1046/j.1365-2656.2001.00524.x/pdf [free pdf]

 

Green, R.H. (1970) On fixed precision level sequential sampling. Researches in Population Ecology 12 (2), 249-251. http://www.springerlink.com/content/g546th1x6n20j2qg/

 

Gilbert, R.O. (1987). Statistical methods for environmental pollution monitoring. Wiley & Sons. http://books.google.co.uk/books?hl=en&lr=&id=lEo1rvDGUEkC&oi=fnd&pg=PA1&ots=F71gTO0Gt4&sig=3vhmsBEYevIqEL9y6VpzmEfPA7M

 

Gill, J.L. (1987). Biases in regression when prediction is inverse to causation. Journal of Animal Science 64 (2), 594-60. http://www.animal-science.org/content/64/2/594.short [free pdf]

 

Hamilton, A. & Versace, V. (2009) Is model II regression necessary for Taylor's Power Law? Potential honours project title . http://www.landfood.unimelb.edu.au/courses/honours/resource_projects.html

 

Hamilton, A.J. & Hepworth, G. (2004). Accounting for cluster sampling in constructing enumerative sequential sampling plans. Journal of Economic Entomology 97 (3), 1132-1136. http://dx.doi.org/10.1603/0022-0493(2004)097[1132:AFCSIC]2.0.CO;2

 

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

 

Hopkins, W.G. (2004). Bias in Bland-Altman but not Regression Validity Analyses. Sportscience 8, 42-46. http://ww.sportsci.org/jour/04/wghbias.htm [free html]

 

Jackson, D.A. & Somers, K.M. (1991). The spectre of 'spurious' correlations. Oecologia 86 (1), 147-151. http://dx.doi.org/ 10.1007/BF00317404 http://labs.eeb.utoronto.ca/jackson/Oecologia86.pdf [free pdf]

 

Kenney, B.C. (1991). Comments on 'Some misconceptions about the spurious correlation problem in the ecological literature' by Y.T. Prairie and D.F. Bird. Oecologia 86 (1), 152. http://dx.doi.org/10.1007/BF00317405

 

Kermack, K.A. & Haldane, J.B.S. (1950). Organic correlation and allometry. Biometrika 37 (1-2), 30-41. http://dx.doi.org/10.1093/biomet/37.1-2.30

 

Kraemer, H.C. (2006). Correlation coefficients in medical research: from product moment correlation to the odds ratio. Statistical Methods in Medical Research 15 (6), 525-545. http://dx.doi.org/DOI: 10.1177/0962280206070650

 

Ludbrook, J. (1997). Comparing methods of measurements. Clinical and Experimental Pharmacology and Physiology 24 (2), 193-203. http://dx.doi.org/10.1111/j.1440-1681.1997.tb01807.x

 

Leng, L. et al. (2007). Ordinary least square regression, orthogonal regression, geometric mean regression and their applications in aerosol science. Journal of Physics: Conference Series 78 012084. http://dx.doi.org/10.1088/1742-6596/78/1/012084 http://www.iop.org/EJ/article/1742-6596/78/1/012084/jpconf7_78_012084.pdf?request-id=21dd0ad8-31c0-4a90-880d-17e1c2f39c7d [free pdf]

 

Ludbrook, J. (2008). Statistics in biomedical laboratory and clinical science: Applications, issues and pitfalls. Medical Principles and Practice 17, 1-13. http://dx.doi.org/10.1159/000109583 http://www.karger.com/Article/Pdf/109583 [free pdf]

 

Ludbrook J. (2002). Statistical techniques for comparing measurers and methods of measurement: a critical review. Clinical and Experimental Pharmacology and Physiology 29(7), 527-36. http://dx.doi.org/10.1046/j.1440-1681.2002.03686.x http://www.cytel.com/papers/Ludbrook-Special-2002.pdf [free pdf]

 

Mcardle, B.H. (1988). The structural relationship: regression in biology. Canadian Journal of Zoology 66, (11) 2329-2339. http://dx.doi.org/10.1139/z88-348

 

Mcardle, B.H. (2004). Lines, models and errors: regression in the field. Limnology and Oceanography 48 (3), 1363-1366. http://www.aslo.org/lo/toc/vol_48/issue_3/1363.pdf [free pdf]

 

Martin, R.F. (2000). General Deming regression for estimating systematic bias and Its confidence interval in method-comparison studies. Clinical Chemistry 46 (1), 100-104. http://www.clinchem.org/cgi/reprint/46/1/100.pdf [free pdf]

 

Maxwell, S.E. et al. (1993) Analysis of covariance and alternatives. In: Edwards, L.K. (Ed.) Applied analysis of variance in behavioral science. Marcel Dekker, New York. [not available in full on line]

 

Mudelsee, M. (2003). Estimating Pearson's correlation coefficient with bootstrap confidence interval from serially dependent time series. Mathematical Geology 35 (6), 651-665. http://dx.doi.org/10.1023/B:MATG.0000002982.52104.02

 

Olds, E.G. (1938). Distribution of sums of squares of rank differences for small numbers of individuals. Annals of Mathematical Statistics 9, 133-148.

 

Pearson, K. (1897). On a form of spurious correlation which may arise when indices are used in the measurement of organs. Proceedings of the Royal Society of London 60, 489-498.

 

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

 

Prairie, Y.T. & Bird, D.F. (1989). Some misconceptions about the spurious correlation problem in the ecological literature. Oecologia 81 (2), 285-288. http://dx.doi.org/10.1007/BF00379817

 

Rodgers, J.L. & Nicewander, W.A. (1988). Thirteen ways to look at the correlation coefficient. The American Statistician 42 (1), 59-66. http://www.jstor.org/pss/2685263 http://data.psych.udel.edu/laurenceau/PSYC861Regression%20Spring%202012/READINGS/rodgers-nicewander-1988-r-13-ways.pdf [free pdf]

 

Ricker, W.E. (1984). Computation and use of central trend lines. Canadian Journal of Zoology 62 (10), 1897-1905. http://dx.doi.org/10.1139/z84-279

 

Ryan, S.E. & Porth, L.S. (2007) A tutorial on the piecewise regression approach applied to bedload transport data. General Technical Report RMRS-GTR-189. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 41 pp. http://www.fs.fed.us/rm/pubs/rmrs_gtr189.pdf [free pdf]

 

Sen, P.K. (1968). Estimates of the regression coefficient based on Kendall's Tau. American Statisatics Journal 63 (324).

 

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

 

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

 

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.

 

Stockl, D. et al. (1998). Validity of linear regression in method comparison studies: is it limited by the statistical model or the quality of the analytical input data. Clinical Chemistry 44, 2340-2346 http://www.clinchem.org/cgi/reprint/44/11/2340.pdf [free pdf]

 

Trexler, J.C. & Travis, J. (1993). Nontraditional regression analyses. Ecology 74, 1629-1637. http://dx.doi.org/10.2307/1939921 http://www.fiu.edu/~trexlerj/nontraditional_regression.pdf [free pdf]

 

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

 

Westgard, J.O. (1998). Points of Care in Using Statistics in Method Comparison Studies (Editorial). Clinical Chemistry 44 (11), 2240-2241. http://www.clinchem.org/cgi/reprint/44/11/2240.pdf [free pdf]

 

Wharton, D. et al. (2005). Bivariate line fitting methods for allometry. Biological Reviews 81 (2), 259-291. http://dx.doi.org/10.1017/S1464793106007007 http://www.maths.unsw.edu.au/sites/default/files/preprint-2005-02_0_0.pdf [free pdf]

 

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