Review of a Research Protocol Prepared by the University of Utah Letter Report (2002) / Chapter Skim
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Appendixes
Appendixes
Pages 12-20
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From page 12... ...
states that the team would consist of a nurse practitioner or physician's assistant and a certified sonographer. Neither of the latter is necessarily a medical doctor, and neither necessarily specializes in thyroid disease.
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In view of the likely marginal statistical power of the study, a thorough discussion, ant] preferably a quantitative evaluation, of potential sources of bias is essential, even for small potential biases.
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It focuses on shared error in radiation-dose estimates for such studies as the Hanford Thyroid Disease Study or the Utah Thyroid Cohort Study, which use a complex dosimetry system that produces multiple replications of possible dose for the cohort. ~ argue that a simple estimation of shared multiplicative error components via direct examination of the replications of dose for each person provides information useful for estimating the power of a study to detect a radiation effect.
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From page 15... ...
for all N subjects in the study. Because many replications, r, are available, we can calculate for each subject, i, the expectec3 value of the unknown true dose, Xi, given the input data, Wj, available for the subject simply as the average of that subjects simulated Xi.
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From page 16... ...
4. However, it is the upper bounds of IBM, and not the lower bounds, that are most affected; in particular, a confidence interval ignoring dosimetry error that does not overlap O will not overlap O once the shared errors in the dosimetry are properly handled.
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From page 17... ...
The naive critical value may be used here because of observation 1 above. The number of times that the test statistic falls into the critical region is tabulated and used to compute an approximate power of the test.
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From page 18... ...
or for models with many background risk parameters or many interactions between dose-response relation and other factors, it might be infeasible to consider construction of confidence intervals in the manner described above. We outline briefly here a simulation-based approach for maximal likelihood that in principle can be used both to approximate maximal likelihood estimates and to construct approximations to full likelihood-based confidence limits (based on the change in the log-likelihood)
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From page 19... ...
Rejection techniques, such as the Metropolis Hastings aIgorithm, can in principle be usecl to transform samples from the conclitional clistribution given only W to the appropriate distribution, thereby allowing implementation of the relatively complex simuiation-basecI schemes. The basic idea is as follows.
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From page 20... ...
3 ~ in Fallout Following Nevada Atmospheric Nuclear Bomb Tests: A Report from the National Cancer Institute. Bethesda, MD: National Cancer Institute.
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