RESEARCH ARTICLE
The Variance of the Number of Effects in an Epidemiological Cohort - The Role of Dose Uncertainty
Guthrie Miller*
Los Alamos National Laboratory, 1619 Central Avenue, MS A117, Los Alamos, NM 87545, USA
Article Information
Identifiers and Pagination:
Year: 2008Volume: 1
First Page: 48
Last Page: 52
Publisher Id: TOEPIJ-1-48
DOI: 10.2174/1874297100801010048
Article History:
Received Date: 04/03/2008Revision Received Date: 09/08/2008
Acceptance Date: 14/08/2008
Electronic publication date: 15/10/2008
Collection year: 2008
© 2008 Guthrie Miller
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Two basic formulas, for the mean and variance of the number of effects in an epidemiological cohort, are derived. The formula for variance shows “extra-binomial variation” or “overdispersion” when there is correlated uncertainty of the probability of an effect. The formulas were validated by a numerical Monte Carlo study. The method of including “epistemic” uncertainty discussed by Hofer (E. Hofer, Health Physics, 2007) is generalized to include separately uncertainty from a Bayesian posterior distribution when the prior is known, and uncertainty of the prior.
