New PDF release: A Dictionary of Epidemiology, 4th edition

By John M. Last

ISBN-10: 0195141687

ISBN-13: 9780195141689

ISBN-10: 0195141695

ISBN-13: 9780195141696

Dictionary making by no means ends simply because languages are continually altering. established through the international, this ebook will proceed to function the normal English-language dictionary of epidemiology in its Fourth variation. It covers the entire universal phrases utilized in epidemiology and plenty of from similar fields akin to biostatistics, infectious ailment keep an eye on, well-being promoting, genetics, scientific epidemiology, overall healthiness economics, and scientific ethics. The definitions are transparent and concise, yet there's house for a few short essays and discussions of the provenance of vital phrases. subsidized through the foreign Epidemiological organization, the dictionary represents the consensus of epidemiologists in lots of various nations. the entire definitions have been reviewed time and again via a global community of participants from each significant department of epidemiology. they're authoritative with no being authoritarian. The Fourth variation comprises good over a hundred and fifty new entries and gigantic revisions of concerning the comparable variety of definitions, plus a dozen new illustrations. some of the new phrases relate to equipment utilized in environmental and scientific epidemiology.

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Sample text

The theorem can also be used for estimating exposure-specific rates from case control studies if there is added information about the overall rate of disease in that population. Some of the terms in the theorem are named. The probability of disease given the symptom is the posterior probability. It is an estimate of the probability of disease posterior to knowing whether or not the symptom was present. The overall probability of disease among the population or our guess of the probability of disease before knowing of the presence or absence of the symptom is the PRIOR PROBABILITY.

AIDS in the World II. New York: Oxford University Press, 1996, p. 47. where D = disease, S = symptom, and D = no disease. The formula emphasizes what clinical intuition often overlooks, namely, that the probability of disease given this symptom depends not only on how characteristic that symptom is of the disease but also on how frequent the disease is among the population being served. The theorem can also be used for estimating exposure-specific rates from case control studies if there is added information about the overall rate of disease in that population.

This effect need not be the sole result of the one cause. A cause is termed "sufficient" when it inevitably initiates or produces an effect. Any given cause may be necessary, sufficient, neither, or both. These possibilities are explained below. Four conditions under which independent variable X may cause Y: 1. 2. 3. 4. variable X mav cause Y Xis Xis necessary sufficient + + + + — — 1. Xis necessary and sufficient to cause Y. Both Xand Fare always present together, and nothing but Xis needed to cause Y; X—»F.

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A Dictionary of Epidemiology, 4th edition by John M. Last


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