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The main issues in such studies are the estimation of mean population healthcare costs and finding the best relationship between costs and covariates through regression modeling [1].
One of the issues in such studies is how to decide on how many of the top candidates are significant.
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Because of these high non-participation rates, selection bias could be a serious issue in such studies.
Although undiagnosed diabetes might not be an issue in such studies, the results of prediction models would apply to similarly screened populations.
Another important issue in such studies is the method used to define the feature-sensitive region within which the response to attention is measured.
An issue in such studies is that phenotypes are often measured by different instruments across study cohorts, requiring harmonization of measures so that more powerful fixed effect meta-analyses can be employed.
While the accuracy of individuals' recall is an issue in such studies, the choice of a suitable control group (comprising individuals undergoing medial unicompartmental arthroplasty) is likely to have minimised recall bias.
In the context of increasing global attention to ethical oversight of biomedical research [ 21- 23], this paper sets out to explore the ethical issues involved in such studies.
The typical issues to be dealt with in such studies are discussed: complexity, scale, testing methods and their mutual relations.
Privacy issues are the major obstacle in such studies: neither biobanks nor research institutions can give out data without explicit consent from the patients or explicit decision by a relevant ethics committee.
The use of animal models is essential in the study of many human disorders, especially in the occasions when human patients are inaccessible, or ethical issue prevents using human subjects in such studies.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com