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Some effects of exposure misclassification on epidemiological studies

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Title
Some effects of exposure misclassification on epidemiological studies
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Zou
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Jun
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1969-
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Jun Zou
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author
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GEORGE
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GEORGE RHOADS
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chair
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LIN
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YONG
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YONG LIN
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internal member
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Demissie
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Kitaw Demissie
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Kitaw Demissie Demissie
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Advisory Committee
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internal member
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Masaki
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Kamal
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Kamal Masaki
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Advisory Committee
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outside member
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Rutgers University
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degree grantor
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Graduate School - New Brunswick
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theses
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2017
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2017-05
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2017
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xx
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eng
Abstract (type = abstract)
In many epidemiological studies the risk factor or exposure of interest is measured with significant error. In well-designed studies this error is non-differential with respect to the outcome, but it nevertheless makes it more difficult to detect associations and it biases estimates of effect toward the null. Less well recognized is that it increases the probability that a significant result, when found, will be a false positive. This is obvious if one considers the extreme example where the observed measure bears little association with the true value and is essentially random, in which case any significant result would have to be an alpha error. The traditional error model is not realistic in the presence of substantial error because with a fixed observed variance and a large error variance, the parameter variance is constrained. We propose a bivariate normal model, which makes fewer assumptions than the traditional model and does not constrain the underlying “true” variance. The model implies the need for larger sample sizes to assure that an effect associated with a misclassified variable is sufficiently unlikely to have occurred by chance that it implies the underlying true variable also shows the effect. A minimal estimate of misclassification can be obtained from the correlation between repeated measurements. When this correlation is low it implies a low correlation of the measurement with the true value and the need for large sample size increases that may make the use of such variables impractical. We use data from the Honolulu Heart Program, a large prospective study of cardiovascular disease to show that risk factors for heart attacks that have stood the test of time mostly are repeatable across a two- years time span with correlations exceeding 0.7. Other risk factors such as diet and physical activity that are believed to cause heart attacks but have been difficult to demonstrate within homogeneous populations have substantially lower repeatability correlations. These considerations emphasize the importance of good measurement of exposure in epidemiological studies.  
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Topic
Public Health
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Rutgers University Electronic Theses and Dissertations
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ETD_7904
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electronic resource
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application/pdf
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text/xml
Extent
1 online resource (viii, 75 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Subject (authority = ETD-LCSH)
Topic
Epidemiology
Note (type = statement of responsibility)
by Jun Zou
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Graduate School - New Brunswick Electronic Theses and Dissertations
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rucore19991600001
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Identifier (type = doi)
doi:10.7282/T3JM2DKM
Genre (authority = ExL-Esploro)
ETD doctoral
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The author owns the copyright to this work.
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Name
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Zou
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Jun
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Permission or license
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2017-03-24 16:35:18
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Jun Zou
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Rutgers University. Graduate School - New Brunswick
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Author Agreement License
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I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
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DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2017-05-31
DateTime (encoding = w3cdtf); (qualifier = exact); (point = end)
2019-05-31
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Embargo
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after May 31st, 2019.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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