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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. [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). [free pdf]


Armitage, P. (2001). Theory and practice in medical statistics. Statistics in Medicine 20 (17-18), 2537-2548.


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. [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). [free pdf]


Bauchau, V. (1997). Is there a "file drawer problem" in biological research. Oikos 79 (2), 407-409.


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.


Bowling, A. (2005). Mode of questionnaire administration can have serious effects on data quality. Journal of Public Health 27 (3), 281-291. [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.


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.


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.


Day, S. et al. (1998). Double data entry: what value, what price? Controlled Clinical Trials 19 (1), 15-24.


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. [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.;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. [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. [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.


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.


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).


Gooderham, P. (2009).. Changing the face of whistleblowing (Editorial). BMJ 338: b2090


Gotzsche, P.C. (2006). Believability of relative risks and odds ratios in abstracts: cross sectional study. BMJ 333, 231-234 (29 July). [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. [free pdf]


Hand, D. (2007). Deception and dishonesty with data: fraud in science. Significance, 4(1), 22-25.


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. [free pdf]


Quotation on p35 in Kinsey et al. (1948). Sexual behaviour in the human male. Saunders, Philadelphia. (extracts)


Knatterud, G.L. (2002). Management and conduct of randomized controlled trials. Epidemiologic Reviews 24 (1), 12-25. [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.


Quotation in Part III, Chapter X in Lippmann, W. (1922). Public Opinion [free text]


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


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. [free pdf]


Lobo, J.M. (2008). More complex distribution models or more representative data? Biodiversity Informatics 5, 14-19. [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.


Martin, B. (1992). Scientific fraud and the power structure of science. Prometheus 10 (1), 83-98. [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. [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. [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. [free pdf]


Obuchowski, N.A. et al. (2004). ROC curves in clinical chemistry: Uses, misuses, and possible solutions. Clinical Chemistry 50 (7), 1118-1125. [free pdf]


Peduzzi, P. et al (2002). Analysis of randomized controlled trials. Epidemiologic Reviews 24 (1), 26-38. [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.


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). [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.


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).


Shaw, R.G. & Mitchell-Olds, T. (1993). ANOVA for unbalanced data: An overview. Ecology 74 (6), 1638-1645.


Shearer, P.R. (1973). Missing data in quantative designs. Applied Statistics 22 (2), 50-58.


Stephan, C. et al. (2003). Comparison of eight computer programs for receiver-operating characteristic analysis. Clinical Chemistry 49, 433-439. [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). [free pdf]


Townsend Peterson, A. et al. (2008). Rethinking receiver operating characteristic analysis applications in ecological niche modeling Ecological Modelling 213 (1), 63-72. [free pdf]


Tupper, M.F. Of truth in things false. In: Proverbial Philosophy, published 1838-1842. [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.