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International Journal of Epidemiology 2006 35(3):775-777; doi:10.1093/ije/dyl055
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Published by Oxford University Press on behalf of the International Epidemiological Association © The Author 2006; all rights reserved.

Commentary

Commentary: On Bayesian perspectives for epidemiological research

James R Carpenter

London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT, UK. E-mail: james.carpenter@lshtm.ac.uk

The first 10% of the full text of this article appears below.

Prevention is better and cheaper than cure, and the contribution of epidemiology to public health has been immense. Yet, when the number of practising epidemiologists is probably at an all time high, the discipline suffers angst.1–3 Why is this, and what should be done?

Arguably, at a time when typical exposure effects are likely to be smaller, so the potential for being mistaken about exposure risks larger, the number of studies and (fuelled by the pressure to publish) the number of articles they generate is increasing. The result is more ‘false-positive’ results published, and an increasingly sceptical reception to all publications.4

Greenland lays into frequentist inference with . . . [Full Text of this Article]


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S. Greenland
Response: Bayesian perspectives for epidemiological research
Int. J. Epidemiol., June 1, 2006; 35(3): 777 - 778.
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