Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
BMC Medicine
Published in: BMC Medicine 1/2011

Open Access 01-12-2011 | Debate

Significance testing as perverse probabilistic reasoning

Authors: M Brandon Westover, Kenneth D Westover, Matt T Bianchi

Published in: BMC Medicine | Issue 1/2011

Login to get access

Abstract

Truth claims in the medical literature rely heavily on statistical significance testing. Unfortunately, most physicians misunderstand the underlying probabilistic logic of significance tests and consequently often misinterpret their results. This near-universal misunderstanding is highlighted by means of a simple quiz which we administered to 246 physicians at two major academic hospitals, on which the proportion of incorrect responses exceeded 90%. A solid understanding of the fundamental concepts of probability theory is becoming essential to the rational interpretation of medical information. This essay provides a technically sound review of these concepts that is accessible to a medical audience. We also briefly review the debate in the cognitive sciences regarding physicians' aptitude for probabilistic inference.
Appendix
Available only for authorised users
Literature
1.
Olser W, Silverman M, Murray T, Bryan C: The Quotable Osler. 2003, Philadelphia: ACP Press
2.
Horton NJ, Switzer SS: Statistical methods in the journal. The New England Journal of Medicine. 2005, 353 (18): 1977-1979. 10.1056/NEJM200511033531823.PubMed
3.
Altman DG, Bland JM: Improving doctors' understanding of statistics. Journal of the Royal Statistical Society. Series A (Statistics in Society). 1991, 154 (2): 223-267. 10.2307/2983040.
4.
Windish DM, Huot SJ, Green ML: Medicine residents' understanding of the biostatistics and results in the medical literature. The Journal of the American Medical Association. 2007, 298 (9): 1010-1022. 10.1001/jama.298.9.1010.PubMed
5.
Ioannidis JPA: Why most published research findings are false. PLoS Medicine. 2005, 2 (8): e124-10.1371/journal.pmed.0020124.PubMedPubMedCentral
6.
Friedman SB, Phillips S: What's the difference? Pediatric residents and their inaccurate concepts regarding statistics. Pediatrics. 1981, 68 (5): 644-646.PubMed
7.
Goodman SN: Toward evidence-based medical statistics. 1: the P value fallacy. Annals of Internal Medicine. 1999, 130 (12): 995-1004.PubMed
8.
9.
Casscells W, Schoenberger A, Graboys TB: Interpretation by physicians of clinical laboratory results. The New England Journal of Medicine. 1978, 299 (18): 999-1001. 10.1056/NEJM197811022991808.PubMed
10.
11.
Eddy DM: Probabilistic Reasoning in Clinical Medicine: Problems and Opportunities. 1982, Cambridge, UK: Cambridge University Press, 249-267.
12.
13.
Falk R, Greenbaum CW: Significance tests die hard: the amazing persistence of a probabilistic misconception. Theory Psychology. 1995, 5: 75-98. 10.1177/0959354395051004.
14.
15.
Gill J: The insignificance of null hypothesis significance testing. Political Research Quarterly. 1999, 52 (3): 647-674.
16.
Gigerenzer G, Murray DJ: Cognition as Intuitive Statistics. 1987, Hillsdale, NJ: L. Erlbaum Associates
17.
Gigerenzer G: The superego, the ego, and the id in statistical reasoning. A Handbook for Data Analysis in the Behavioral Sciences: Methodological Issues. Edited by: Keren G, Lewis C. 1993, Hillsdale, NJ: L. Erlbaum Associates, 574.
18.
Campbell L, Garnett W: The Life of James Clerk Maxwell. With a Selection from His Correspondence and Occasional Writings and a Sketch of His Contributions to Science. 1882, London: Macmillan and Co
19.
Mumford D: The dawning of the age of stochasticity. Mathematics: Frontiers and Perspectives. 2000, 197-218.
20.
Oaksford M, Chater N: Bayesian Rationality: The Probabilistic Approach to Human Reasoning. 2007, Oxford: Oxford University Press, [Oxford Cognitive Science Series]
21.
Jaynes ET, Bretthorst GL: Probability Theory: The Logic of Science. 2003, Cambridge, UK: Cambridge University Press
22.
Cox RT: The Algebra of Probable Inference. 1961, Baltimore: Johns Hopkins Press
23.
Jaynes ET: How does the brain do plausible reasoning?. Maximum-Entropy and Bayesian Methods in Science and Engineering. Edited by: Erickson GJ, Smith CR. 1988, Kluwer Academic Publishers
24.
Horn KSV: Constructing a logic of plausible inference: a guide to Cox's theorem. International Journal of Approximate Reasoning. 2003, 34: 3-24. 10.1016/S0888-613X(03)00051-3.
25.
Kruschke JK: Doing Bayesian Data Analysis: A Tutorial with R and BUGS. 2010, Academic Press
26.
Kruschke JK: Bayesian data analysis. Wiley Interdisciplinary Reviews: Cognitive Science. 2010, 1 (5): 658-676. 10.1002/wcs.72.PubMed
27.
Fisher RA: Statistical Methods and Scientific Inference. 1973, New York: Hafner Press, 3, rev. and enl
28.
Kruschke JK: What to believe: Bayesian methods for data analysis. Trends in Cognitive Sciences. 2010, 14 (7): 293-300. 10.1016/j.tics.2010.05.001.PubMed
29.
Gelman A: Bayesian Data Analysis. 2004, Boca Raton, Fla: Chapman & Hall/CRC, [Texts in Statistical Science], 2
30.
Diamond GA, Kaul S: Prior convictions: Bayesian approaches to the analysis and interpretation of clinical megatrials. Journal of the American College of Cardiology. 2004, 43 (11): 1929-1939. 10.1016/j.jacc.2004.01.035.PubMed
31.
Berry DA: Bayesian clinical trials. Nature Reviews. Drug Discovery. 2006, 5: 27-36. 10.1038/nrd1927.PubMed
32.
Goodman SN: Introduction to Bayesian methods I: measuring the strength of evidence. Clinical Trials (London, England). 2005, 2 (4): 282-290. discussion 301-304, 364-378
33.
Berry DA: Introduction to Bayesian methods III: use and interpretation of Bayesian tools in design and analysis. Clinical Trials (London, England). 2005, 2 (4): 295-300. discussion 301-304, 364-378
34.
Louis TA: Introduction to Bayesian methods II: fundamental concepts. Clinical Trials (London, England). 2005, 2 (4): 291-294. discussion 301-304, 364-378
35.
Spiegelhalter DJ, Myles JP, Jones DR, Abrams KR: Bayesian methods in health technology assessment: a review. Health Technology Assessment (Winchester, England). 2000, 4 (38): 1-130.
36.
Spiegelhalter DJ, Myles JP, Jones DR, Abrams KR: Methods in health service research. An introduction to Bayesian methods in health technology assessment. British Medical Journal (Clinical Research Ed.). 1999, 319 (7208): 508-512.
37.
Jacobs RA, Kruschke JK: Bayesian learning theory applied to human cognition. Wiley Interdisciplinary Reviews: Cognitive Science. 2010, 2: 8-21. 10.1002/wcs.80.PubMed
38.
Chater N, Manning CD: Probabilistic models of language processing and acquisition. Trends in Cognitive Sciences. 2006, 10 (7): 335-344. 10.1016/j.tics.2006.05.006.PubMed
39.
Chater N, Oaksford M: The Probabilistic Mind: Prospects for Bayesian Cognitive Science. 2008, Oxford: Oxford University Press
40.
Tenenbaum JB, Griffiths TL, Kemp C: Theory-based Bayesian models of inductive learning and reasoning. Trends in Cognitive Sciences. 2006, 10 (7): 309-318. 10.1016/j.tics.2006.05.009.PubMed
41.
Xu F, Tenenbaum JB: Word learning as Bayesian inference. Psychological Review (New York). 2007, 114 (2): 245.
42.
Steyvers M, Griffiths TL, Dennis S: Probabilistic inference in human semantic memory. Trends in Cognitive Sciences. 2006, 10 (7): 327-334. 10.1016/j.tics.2006.05.005.PubMed
43.
Manning CD, Schütze H: Foundations of Statistical Natural Language Processing. 1999, MIT Press
44.
Westover M, O'Sullivan J: Achievable rates for pattern recognition. Information Theory, IEEE Transactions on. 2008, 54: 299-320. 10.1109/TIT.2007.911296.
45.
Yuille A, Kersten D: Vision as Bayesian inference: analysis by synthesis?. Trends in Cognitive Sciences. 2006, 10 (7): 301-308. 10.1016/j.tics.2006.05.002.PubMed
46.
Grenander U, Miller M: Pattern Theory: From Representation to Inference. 2007, USA: Oxford University Press
47.
Jordan MI, (Ed): Learning in Graphical Models. 1998, The MIT Press, 1
48.
Bishop CM: Pattern Recognition and Machine Learning. 2007, Springer, 1
49.
Mumford D, Desolneux A: Pattern Theory: The Stochastic Analysis of Real-World Signals (Applying Mathematics). 2010, Natick, Mass.: A K Peters
50.
MacKay DJC: Information Theory, Inference & Learning Algorithms. 2002, Cambridge University Press, 1
51.
Frey BJ: Graphical Models for Machine Learning and Digital Communication. 1998, The MIT Press
52.
Jelinek F: Statistical Methods for Speech Recognition. 1998, The MIT Press
53.
Pearl J: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. 1998, San Francisco, Calif: Morgan Kaufmann, [The Morgan Kaufmann Series in Representation and Reasoning], Rev. 2nd printing
54.
Paté-Cornell E, Guikema S: Probabilistic modeling of terrorist threats: a systems analysis approach to setting priorities among countermeasures. Military Operations Research. 2002, 7 (4): 5-20.
55.
Forrester M, Pettitt A, Gibson G: Bayesian inference of hospital-acquired infectious diseases and control measures given imperfect surveillance data. Biostatistics. 2007, 8 (2): 383-10.1093/biostatistics/kxl017.PubMed
56.
de Campos L, Fernández-Luna J, Huete J: Bayesian networks and information retrieval: an introduction to the special issue. Information Processing & Management. 2004, 40 (5): 727-733.
57.
Kolmogorov AN: Foundations of the Theory of Probability. 1956, New York: Chelsea Pub. Co, 2d english
58.
Bayes T: An essay towards solving a problem in the doctrine of chances. Philosophical Transactions of the Royal Society. 1763, 53: 370-418. 10.1098/rstl.1763.0053.
59.
Gigerenzer G, Swijtink Z, Porter T, Daston L, Beatty J, Kruger L: The Empire of Chance: How Probability Changed Science and Everyday Life (Ideas in Context). 1989, Cambridge [Cambridgeshire]: Cambridge University Press
60.
Krüger L: The Probabilistic Revolution. 1987, Cambridge, Mass: MIT Press
61.
62.
63.
Browner WS, Newman TB: Are all significant P values created equal? The analogy between diagnostic tests and clinical research. The Journal of the American Medical Association. 1987, 257 (18): 2459-2463. 10.1001/jama.257.18.2459.PubMed
64.
65.
66.
Dixon P: The p-value fallacy and how to avoid it. Canadian Journal of Experimental Psychology = Revue Canadienne De Psychologie Exp'erimentale. 2003, 57 (3): 189-202.
67.
Frick RW: The appropriate use of null hypothesis testing. Psychological Methods. 1996, 1 (4): 379-390. 10.1037/1082-989X.1.4.379.
68.
Hagen RL: In praise of the null hypothesis statistical test. American Psychologist. 1997, 52: 15-24. 10.1037/0003-066X.52.1.15.
69.
Killeen PR: An alternative to null-hypothesis significance tests. Psychological Science: A Journal of the American Psychological Society/APS. 2005, 16 (5): 345-353. [PMID: 15869691]
70.
Killeen ACO, jan Wagenmakers E, Grünwald P: A Bayesian perspective on hypothesis testing. Psychological Science. 2006, 17: 10.1111/j.1467-9280.2006.01758.x.
71.
Loftus GR: Psychology will be a much better science when we change the way we analyze data. Current Directions in Psychological Science. 1996, 5 (6): 161-171. 10.1111/1467-8721.ep11512376. [ArticleType: research-article/Full publication date: Dec., 1996/Copyright © 1996 Association for Psychological Science]
72.
73.
Nickerson RS: Null hypothesis significance testing: a review of an old and continuing controversy. Psychological Methods. 2000, 5 (2): 241-301. 10.1037/1082-989X.5.2.241. [PMID: 10937333]PubMed
74.
Trafimow D: Hypothesis testing and theory evaluation at the boundaries: surprising insights from Bayes's theorem. Psychological Review. 2003, 110 (3): 526-535. 10.1037/0033-295X.110.3.526. [PMID: 12885113]PubMed
75.
Wagenmakers EJ: A practical solution to the pervasive problem of p values. Psychonomic Bulletin & Review. 2007, 14 (5): 779-804.
76.
Wainer H: One cheer for null hypothesis significance testing. Psychological Methods. 1999, 4 (2): 212-213. 10.1037/1082-989X.4.2.212.
77.
Berger JO, Wolpert RL: The Likelihood Principle. 1988, IMS
78.
79.
Royall R: Statistical Evidence: A Likelihood Paradigm. 1997, Chapman & Hall/CRC
80.
Sellke T, Bayarri M, Berger J: Calibration of ρ values for testing precise null hypotheses. The American Statistician. 2001, 55: 62-71. 10.1198/000313001300339950.
81.
Stuart A, Ord J, Arnold S: Kendall's advanced theory of statistics. Vol. 2a: classical inference and the linear model. 1999
82.
Goodman SN: p values, hypothesis tests, and likelihood: implications for epidemiology of a neglected historical debate. American Journal of Epidemiology. 1993, 137 (5): 485-496. discussion 497-501PubMed
83.
Goodman SN: Toward evidence-based medical statistics. 2: the Bayes factor. Annals of Internal Medicine. 1999, 130 (12): 1005-1013.PubMed
84.
Wasserman L: All of Statistics: A Concise Course in Statistical Inference. 2004, New York: Springer, [Springer Texts in Statistics]
85.
Gill J: 'S'attaquer a l'Heritage de Fisher: Comment Tester une Hypothese en Science Sociale: Quelques Commentaires Sur Denis.' (Grappling with Fisher's legacy in social science hypothesis testing: some comments on Denis.). Journal de la Société Franc¸aise de Statistique. 2004, 145: 1-9.
86.
Matthews JR: Quantification and the Quest for Medical Certainty. 1995, Princeton, NJ: Princeton University Press
87.
Marks HM: The Progress of Experiment: Science and Therapeutic Reform in the United States, 1900-1990. 2000, Cambridge, UK: Cambridge University Press, [Cambridge History of Medicine], 1st pbk
88.
Porter TM: Trust in Numbers: The Pursuit of Objectivity in Science and Public Life. 1995, Princeton, NJ: Princeton University Press
89.
90.
Clarke M, Chalmers I: Discussion sections in reports of controlled trials published in general medical journals: islands in search of continents?. The Journal of the American Medical Association. 1998, 280 (3): 280-282. 10.1001/jama.280.3.280.PubMed
91.
Clarke M, Alderson P, Chalmers I: Discussion sections in reports of controlled trials published in general medical journals. The Journal of the American Medical Association. 2002, 287 (21): 2799-2801. 10.1001/jama.287.21.2799.PubMed
92.
Ioannidis JPA, Haidich A, Lau J: Any casualties in the clash of randomised and observational evidence? No - recent comparisons have studied selected questions, but we do need more data. British Medical Journal. 2001, 322 (7291): 879-880. 10.1136/bmj.322.7291.879. [PMC1120057]PubMedPubMedCentral
93.
Lawlor DA, Smith GD, Kundu D, Bruckdorfer KR, Ebrahim S: Those confounded vitamins: what can we learn from the differences between observational versus randomised trial evidence?. Lancet. 2004, 363 (9422): 1724-1727. 10.1016/S0140-6736(04)16260-0.PubMed
94.
Vandenbroucke JP: When are observational studies as credible as randomised trials?. Lancet. 2004, 363 (9422): 1728-1731. 10.1016/S0140-6736(04)16261-2.PubMed
95.
Michiels S, Koscielny S, Hill C: Prediction of cancer outcome with microarrays: a multiple random validation strategy. Lancet. 2005, 365 (9458): 488-492. 10.1016/S0140-6736(05)17866-0.PubMed
96.
Ioannidis JP, Ntzani EE, Trikalinos TA, Contopoulos-Ioannidis DG: Replication validity of genetic association studies. Nature Genetics. 2001, 29 (3): 306-309. 10.1038/ng749.PubMed
97.
Ioannidis JPA: Contradicted and initially stronger effects in highly cited clinical research. The Journal of the American Medical Association. 2005, 294 (2): 218-228. 10.1001/jama.294.2.218.PubMed
98.
Colhoun HM, McKeigue PM, Smith GD: Problems of reporting genetic associations with complex outcomes. Lancet. 2003, 361 (9360): 865-872. 10.1016/S0140-6736(03)12715-8.PubMed
99.
Ioannidis JPA: Genetic associations: false or true?. Trends in Molecular Medicine. 2003, 9 (4): 135-138. 10.1016/S1471-4914(03)00030-3.PubMed
100.
Ioannidis JPA: Microarrays and molecular research: noise discovery?. Lancet. 365 (9458): 454-455.
101.
Neyman J, Pearson ES: On the problem of the most efficient tests of statistical hypotheses. Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character. 1933, 231: 289-337. 10.1098/rsta.1933.0009. [ArticleType: primary article/Full publication date: 1933/Copyright © 1933 The Royal Society]
102.
Strunk A, Bhalla V, Clopton P, Nowak RM, McCord J, Hollander JE, Duc P, Storrow AB, Abraham WT, Wu AHB, Steg G, Perez A, Kazanegra R, Herrmann HC, Aumont MC, McCullough PA, Maisel A: Impact of the history of congestive heart failure on the utility of B-type natriuretic peptide in the emergency diagnosis of heart failure: results from the Breathing Not Properly Multinational Study. The American Journal of Medicine. 2006, 119: 69.e1-11. 10.1016/j.amjmed.2005.04.029. [http://​www.​ncbi.​nlm.​nih.​gov/​pubmed/​16431187]
103.
McCullough PA, Nowak RM, McCord J, Hollander JE, Herrmann HC, Steg PG, Duc P, Westheim A, Omland T, Knudsen CW, Storrow AB, Abraham WT, Lamba S, Wu AHB, Perez A, Clopton P, Krishnaswamy P, Kazanegra R, Maisel AS: B-type natriuretic peptide and clinical judgment in emergency diagnosis of heart failure: analysis from Breathing Not Properly (BNP) Multinational Study. Circulation. 2002, 106 (4): 416-422. 10.1161/01.CIR.0000025242.79963.4C.PubMed
104.
Glimcher PW: Decisions, Uncertainty, and the Brain: The Science of Neuroeconomics. 2003, Cambridge, Mass: MIT Press
105.
Barlow H: Redundancy reduction revisited. Network-Computation in Neural Systems. 2001, 12 (3): 241-253.
106.
Barlow H: The coding of sensory messages. Current Problems in Animal Behavior. Edited by: Thorpe W, Zangwill O. 1961, Cambridge: Cambridge University Press
107.
Barlow H: What is the computational goal of the neocortex?. Large Scale Neuronal Theories of the Brain. Edited by: Koch C, Davis JL. 1994, MIT Press, 1-22.
108.
Knill DC, Richards W: Perception as Bayesian Inference. 1996, Cambridge University Press
109.
Kahneman D, Slovic P, Tversky A: Judgment Under Uncertainty: Heuristics and Biases. 1982, Cambridge: Cambridge University Press
110.
Elstein AS: Heuristics and biases: selected errors in clinical reasoning. Academic Medicine: Journal of the Association of American Medical Colleges. 1999, 74 (7): 791-794.
111.
Dolan JG, Bordley DR, Mushlin AI: An evaluation of clinicians' subjective prior probability estimates. Medical Decision Making. 1986, 6 (4): 216-223. 10.1177/0272989X8600600406.PubMed
112.
Phelps MA, Levitt MA: Pretest probability estimates: a pitfall to the clinical utility of evidence-based medicine?. Academic Emergency Medicine: Official Journal of the Society for Academic Emergency Medicine. 2004, 11 (6): 692-694.
113.
Bornstein BH, Emler AC: Rationality in medical decision making: a review of the literature on doctors' decision-making biases. Journal of Evaluation in Clinical Practice. 2001, 7 (2): 97-107. 10.1046/j.1365-2753.2001.00284.x.PubMed
114.
Dawson N, Arkes H: Systematic errors in medical decision making. Journal of General Internal Medicine. 1987, 2 (3): 183-187. 10.1007/BF02596149.PubMed
115.
Laplace PS: Thérie Analytique Des Probabilités. 1847, Paris: Imprimerie royale
116.
Olshausen BA, Field DJ: Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature. 1996, 381 (6583): 607-609. 10.1038/381607a0.PubMed
117.
Rao RPN, Olshausen BA, Lewicki MS: Probabilistic Models of the Brain: Perception and Neural Function. 2002, The MIT Press
118.
Rieke F: Spikes: Exploring the Neural Code (Computational Neuroscience). 1997, Cambridge, Mass: MIT Press
119.
Koch C, Davis JL: Large-Scale Neuronal Theories of the Brain. 1994, Storming Media
120.
Oaksford M, Chater N: The probabilistic approach to human reasoning. Trends in Cognitive Sciences. 2001, 5 (8): 349-357. 10.1016/S1364-6613(00)01699-5.PubMed
121.
Baker C, Tenenbaum J, Saxe R: Bayesian models of human action understanding. Advances in Neural Information Processing Systems. 2006, 18: 99.
122.
Griffiths TL, Tenenbaum JB: Optimal predictions in everyday cognition. Psychological Science. 2006, 17 (9): 767-773. 10.1111/j.1467-9280.2006.01780.x.PubMed
123.
Edwards AWF: Likelihood. 1992, Baltimore: Johns Hopkins University Press, Expanded
124.
Skellam JG: Models, inference, and strategy. Biometrics. 1969, 25 (3): 457-475. 10.2307/2528899.PubMed
125.
Azizi F, Ghanbarian A, Madjid M, Rahmani M: Distribution of blood pressure and prevalence of hypertension in Tehran adult population: Tehran Lipid and Glucose Study (TLGS), 1999-2000. Journal of Human Hypertension. 2002, 16 (5): 305-312. 10.1038/sj.jhh.1001399.PubMed
126.
Cowie MR, Struthers AD, Wood DA, Coats AJ, Thompson SG, Poole-Wilson PA, Sutton GC: Value of natriuretic peptides in assessment of patients with possible new heart failure in primary care. Lancet. 1997, 350 (9088): 1349-1353. 10.1016/S0140-6736(97)06031-5.PubMed
127.
Leibniz GW: Dissertatio De Arte Combinatoria, in Qua Ex Arithmeticae Fundamentis Complicationum Ac Transpositionum Doctrina Novis Praeceptis Extruitur, & Usus Ambarum Per Universum Scientiarum Orbem Ostenditur; Nova Etiam Artis Meditandi, Seu Logicae Inventionis Semina Sparguntur apud Joh. Simon Fickium et Joh. Polycarp. Seuboldum, Literis Sporelianis: Lipsiae. 1666
128.
Couturat L: La Logique De Leibniz Dapres Des Documents Inedits. 1901, Collection historique des grands philosophes. Paris: F. Alcan
129.
Boole G: An Investigation of the Laws of Thought, on Which Are Founded the Mathematical Theories of Logic and Probabilities. 1961, New York: Dover Publications
130.
Boole G: The Laws of Thought (1854). 1952, La Salle, Ill: The Open Court Pub. Co
Metadata
Title
Significance testing as perverse probabilistic reasoning
Authors
M Brandon Westover
Kenneth D Westover
Matt T Bianchi
Publication date
01-12-2011
Publisher
BioMed Central
Published in
BMC Medicine / Issue 1/2011
Electronic ISSN: 1741-7015
DOI
https://doi.org/10.1186/1741-7015-9-20

Other articles of this Issue 1/2011

BMC Medicine 1/2011 Go to the issue

Research article

Combinations of motor measures more strongly predict adverse health outcomes in old age: the rush memory and aging project, a community-based cohort study

Commentary

Control of tuberculosis in large cities in developed countries: an organizational problem

Review

Closed-loop insulin delivery for treatment of type 1 diabetes

Research article

Diabetes mellitus type 2 and other chronic non-communicable diseases in the central region, Saudi Arabia (riyadh cohort 2): a decade of an epidemic

Research article

Human papillomavirus vaccine introduction in low-income and middle-income countries: guidance on the use of cost-effectiveness models

Debate

'Gut health': a new objective in medicine?