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Statistics bibliography 02 - 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]

 

Al-Marzouki, S. et al. (2005). Are these data real? Statistical methods for the detection of data fabrication in clinical trials. BMJ 331, 267-270 (30 July). http://dx.doi.org/10.1136/bmj.331.7511.267 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1181267/pdf/bmj33100267.pdf [free pdf]

 

Armitage, P. (2001). Theory and practice in medical statistics. Statistics in Medicine 20 (17-18), 2537-2548. http://dx.doi.org/10.1002/sim.727

 

Anonymous (1999). News in brief: Demoted PhD accused of trying to kill whistleblower. Nature 397, 381.

 

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

 

Arts, D.G.T. et al (2002). Defining and improving data quality in medical registries: A literature review, case study, and generic framework. Journal of American Medical Informatics Association 9, 600-611. http://dx.doi.org/10.1197/jamia.M1087 http://www.mums.ac.ir/shares/hisws/hisws/kaiser1.pdf [free pdf]

 

Batini, C. & Scannapieco , M. (2006). Data Quality: Concepts, Methodologies and Techniques (Data-centric Systems and Applications) Springer. 262 pp.

 

Bland, J.M. & Altman, D.G. (2002). Validating scales and indexes. BMJ 324, 606-607 (9 March). http://dx.doi.org/10.1136/bmj.324.7337.606 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1122519/pdf/606.pdf [free pdf]

 

Bauchau, V. (1997). Is there a "file drawer problem" in biological research. Oikos 79 (2), 407-409. http://dx.doi.org/10.2307/3546025

 

Bland, M. (2000). An introduction to medical statistics. 3rd Edition Oxford University Press, Oxford.

 

Bland, J.M. & Altman, D.G. (2007). Agreement between methods of measurement with multiple observations per individual. Journal of Biopharmaceutical Statistics 17 (4), 571-582. http://dx.doi.org/10.1080/10543400701329422

 

Bowling, A. (2005). Mode of questionnaire administration can have serious effects on data quality. Journal of Public Health 27 (3), 281-291. http://dx.doi.org/10.1093/pubmed/fdi031 http://jpubhealth.oxfordjournals.org/cgi/reprint/27/3/281.pdf [free pdf]

 

Broad, W. & Wade, N. (1985). Betrayers of the truth: Fraud and deceit in science. Oxford University Press, Oxford, UK.

 

Brown, N. (1993). Measurement, regression and calibration.(Oxford Statistical Science Series). Clarendon Press

 

Buyse, M. et al. (1999). The role of biostatistics in the prevention, detection and treatment of fraud in clinical trials. Statistics in Medicine 18 (24), 3435-3451. http://www3.interscience.wiley.com/journal/68502845/abstract

 

Barzi, F. et al. (2006). Analysis of the benefits of a Mediterranean diet in the GISSI-Prevenzione study: A case study in imputation of missing values from repeated measurements. European Journal of Epidemiology 21 (1), 15-24. http://dx.doi.org/10.1007/s10654-005-5086-5

 

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

 

Cleveland, W.S. (1985). The elements of graphing data. Wadsworth & Advanced Book Program, Pacific Grove, CA.

 

Csada, R.D. et al. (1996). The "file drawer" problem of non-significant results: does it apply to biological research? Oikos 76 (3), 591-593. http://dx.doi.org/10.2307/3546355

 

Day, S. et al. (1998). Double data entry: what value, what price? Controlled Clinical Trials 19 (1), 15-24. http://dx.doi.org/10.1016/S0197-2456(97)00096-2

 

Ersbøll, A.K. & Ersbøll B.K. (2003). Epidemiological studies based on small sample sizes - a statistician's point of view. Acta Veterinaria Scandinavica 44 (Suppl 1), S127-S140. http://dx.doi.org/10.1186/1751-0147-44-S1-S127 http://actavetscand.com/content/pdf/1751-0147-44-S1-S127.pdf [free pdf]

 

Fanelli, D. (2001). How many scientists fabricate and falsify research? A systematic review and meta-analysis of survey data. PLoS ONE 4 (5), e5738. http://dx.doi.org/doi:10.1371/journal.pone.0005738 http://www.plosone.org/article/fetchObjectAttachment.action;jsessionid=3E594D56DECF723AFCEB6D14DE7012AA?uri=info%3Adoi%2F10.1371%2Fjournal.pone.0005738&representation=PDF[free pdf]

 

Feng, S. et al. (2004). Quality control of daily meteorological data in China, 1951-2000: a new dataset. International Journal Of Climatology 24, 853-870. http://dx.doi.org/10.1002/joc.1047 http://snrs.unl.edu/climate_change/research/China_data_QC.pdf [free pdf]

 

Festing, M.F.W. & Altman, D.G. (2002). Guidelines for the design and statistical analysis of experiments using laboratory animals. ILAR Journal 43 (4), 244-258. http://research.md.kku.ac.th/others/animal/Guidelines-Lab%20animals.pdf [free pdf]

 

Gardner, I.A. & Greiner, M (2006). Receiver-operating characteristic curves and likelihood ratios: improvements over traditional methods for the evaluation and application of veterinary clinical pathology tests. Veterinary Clinical Pathology 35 (1), 8-17. http://dx.doi.org/10.1111/j.1939-165X.2006.tb00082.x

 

Gilbert, N. (2009). Science journals crack down on image manipulation. Nature Published online 9 October 2009 http://dx.doi.org10.1038/news.2009.991

 

Gilchrist, J.M. (2009). Weighted 2×2 kappa coefficients: recommended indices of diagnostic accuracy for evidence-based practice. Journal of Clinical Epidemiology 62 (10), 1045-1053. http://dx.doi.org/10.1016/j.jclinepi.2008.11.012

 

Glantz, S.A. (2005). Primer of biostatistics. McGraw Hill Professional, New York.

 

Grimes, D.A. & Schulz, K.F. (2002). Refining clinical diagnosis with likelihood ratios. Lancet 365, 1500-1505 (23 April). http://dx.doi.org/10.1016/S0140-6736(05)66422-7

 

Gooderham, P. (2009).. Changing the face of whistleblowing (Editorial). BMJ 338: b2090 http://dx.doi.org/10.1136/bmj.b2090

 

Gotzsche, P.C. (2006). Believability of relative risks and odds ratios in abstracts: cross sectional study. BMJ 333, 231-234 (29 July). http://dx.doi.org/10.1136/bmj.38895.410451.79 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1523498/pdf/bmj33300231.pdf [free pdf]

 

Grayson, L. (1995). Scientific deception: an overview and guide to the literature of misconduct and fraud in scientific research. The British Library, London.

 

Gott, R. & Duggan, S. (2003). Understanding and using scientific evidence. Sage Publications, London.

 

Halligan, S. (2002). Reproducibility, repeatability, correlation and measurement error. (Letter) The British Journal of Radiology 75, 193-195. http://bjr.birjournals.org/cgi/reprint/75/890/193.pdf [free pdf]

 

Hand, D. (2007). Deception and dishonesty with data: fraud in science. Significance, 4(1), 22-25. http://dx.doi.org/10.1111/j.1740-9713.2007.00215.x http://www.blackwell-synergy.com/doi/pdf/10.1111/j.1740-9713.2007.00215.x

 

Horton, N.J. & Kleinman, K.P. (2007). Much ado about nothing: A comparison of missing data methods and software to fit incomplete data regression models. The American Statistician 61 (1), 79-90. http://dx.doi.org/10.1198/000313007X172556 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1839993/pdf/nihms16073.pdf [free pdf]

 

Quotation on p35 in Kinsey et al. (1948). Sexual behaviour in the human male. Saunders, Philadelphia. http://books.google.co.uk/books?id=pfMKrY3VvigC&pg=PP1&dq=Kinsey++Sexual+behaviour+in+the+human+male&sig=DDqBHljijlfowwKkFgGGcifwjsc (extracts)

 

Knatterud, G.L. (2002). Management and conduct of randomized controlled trials. Epidemiologic Reviews 24 (1), 12-25. http://epirev.oxfordjournals.org/cgi/reprint/24/1/12 [free pdf]

 

Levitas, R. & Guy, W. (Eds) (1999). Interpreting official statistics. Routledge, London.

 

Lin, L.I. (1989). A concordance correlation coefficient to evaluate reproducibility. Biometrics 45 (1), 255-268. http://dx.doi.org/10.2307/2532051

 

Quotation in Part III, Chapter X in Lippmann, W. (1922). Public Opinion http://www.gutenberg.org/dirs/etext04/pbpnn10.txt [free text]

 

List, C.J. (1985). Scientific fraud: Social deviance or the failure of virtue? Science, Technology & Human Values 10 (4), 27-36. http://www.jstor.org/pss/689361

 

Little, R.J.A. & Rubin, D.B. (1987). Statistical analysis with missing data. Wiley New York, USA.

 

Lobo, J.M. (2007). AUC: a misleading measure of the performance of predictive distribution models. Global Ecology and Biogeography 17 (2), 691-692. http://dx.doi.org/10.1111/j.1466-8238.2007.00358.x http://www2.unil.ch/biomapper/Download/Lobo-GloEcoBioGeo-2007.pdf [free pdf]

 

Lobo, J.M. (2008). More complex distribution models or more representative data? Biodiversity Informatics 5, 14-19. https://journals.ku.edu/index.php/jbi/article/viewFile/40/1550 [free pdf]

 

Mahoney, M.J. (1977). Publication prejudices: An experimental study of confirmatory bias in the peer review system. Cognitive Therapy and Research 1 (2), 161-175. http://dx.doi.org/10.1007/BF01173636

 

Martin, B. (1992). Scientific fraud and the power structure of science. Prometheus 10 (1), 83-98. http://www.bmartin.cc/pubs/92prom.html [free html]

 

McKee, M. (2007). Cochrane on Communism: the influence of ideology on the search for evidence. International Journal of Epidemiology 36 (2), 269-273. http://dx.doi.org/10.1093/ije/dym002 http://ije.oxfordjournals.org/cgi/reprint/dym002v1.pdf [free pdf]

 

McKnight, P. M et al. (2007). Missing data: A gentle introduction. Guilford Press.

 

Milliken, G. A., & Johnson, D. E. (1992). Analysis of messy data: Vol. I. Designed experiments. Chapman & Hall, New York.

 

Michels, K.B (2001). A renaissance for measurement error. (Editorial). International Journal of Epidemiology 30 (3), 421-422. http://ije.oxfordjournals.org/cgi/reprint/30/3/421.pdf [free pdf]

 

Myles, P.S. & Cui, J. (2007). Using the Bland-Altman method to measure agreement with repeated measures. British Journal of Anaesthesia 99 (3), 309-311. http://dx.doi.org/10.1093/bja/aem214 http://bja.oxfordjournals.org/cgi/reprint/99/3/309.pdf [free pdf]

 

Obuchowski, N.A. et al. (2004). ROC curves in clinical chemistry: Uses, misuses, and possible solutions. Clinical Chemistry 50 (7), 1118-1125. http://dx.doi.org/10.1373/clinchem.2004.031823 http://www.clinchem.org/cgi/reprint/50/7/1118.pdf [free pdf]

 

Peduzzi, P. et al (2002). Analysis of randomized controlled trials. Epidemiologic Reviews 24 (1), 26-38. http://dx.doi.org/10.1093/epirev/24.1.26 http://epirev.oxfordjournals.org/cgi/reprint/24/1/26.pdf [free pdf]

 

Planck, M. (1936) The philosophy of physics. W.W. Norton & Co.

 

Phelps, E.J. (1899). Speech at Mansion House (24 Jan. 1899). Quoted from Quote Geek. http://www.quotegeek.com

 

Reid, M.C. et al. (1995). Use of methodological standards in diagnostic test research. Getting better but still not good. JAMA 274, 645-651 (23 August). http://jama.ama-assn.org/cgi/content/abstract/274/8/645 [abstract only]

 

Relman, A. (2001). Trust me, I'm a scientist. New Scientist 171 (2309), 46-47 (22 September).

 

Remarque, E.M. (1956): Der schwarze Obelisk.

The quotation from this book attributed to Stalin was: "Aber das ist wohl so, weil ein einzelner immer der Tod ist - und zwei Millionen immer nur eine Statistik."

 

Rubin D.B. (1976). Inference and missing data. Biometrika 63 (3), 581-92. http://dx.doi.org/10.1093/biomet/63.3.581

 

Sackett, D.L. & Strauss, S.(1998). On some clinically useful measures of the accuracy of diagnostic tests. Evidence-Based Medicine 3, 68-70.

 

Schulz, K.F. & Grimes, D.A. (2002). Sample size slippages in randomised trials: exclusions and the lost and wayward. Lancet 359, 781-785 (2 March). http://dx.doi.org/10.1016/S0140-6736(02)07882-0

 

Shaw, R.G. & Mitchell-Olds, T. (1993). ANOVA for unbalanced data: An overview. Ecology 74 (6), 1638-1645. http://dx.doi.org/10.2307/1939922

 

Shearer, P.R. (1973). Missing data in quantative designs. Applied Statistics 22 (2), 50-58. http://dx.doi.org/10.2307/2346915

 

Stephan, C. et al. (2003). Comparison of eight computer programs for receiver-operating characteristic analysis. Clinical Chemistry 49, 433-439. http://www.clinchem.org/cgi/reprint/49/3/433.pdf [free pdf]

 

Sterne, J.A.C. et al. (2009). Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls.BMJ 339, b2651 (18 July). http://dx.doi.org/10.1136/bmj.b2393 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2714692/?report=printable [free pdf]

 

Townsend Peterson, A. et al. (2008). Rethinking receiver operating characteristic analysis applications in ecological niche modeling Ecological Modelling 213 (1), 63-72. http://dx.doi.org/10.1016/j.ecolmodel.2007.11.008 http://www.whoi.edu/cms/files/Ecological_Modelling_2008_Peterson_53562.pdf [free pdf]

 

Tupper, M.F. Of truth in things false. In: Proverbial Philosophy, published 1838-1842. http://books.google.com/books?hl=en&lr=&id=ZbQDAAAAQAAJ&oi=fnd&pg=PA62&ots=jB2hoxhTS2&sig=pzlFKv_GM91pKOiDsB0Dy_KayT0 [extracts]

 

Vandenbroucke, J.P. (1990). How trustworthy is epidemiologic research. Epidemiology 1 (1), 83-84.

 

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