Ronald Curtis Eldridge

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Common genetic variants contribute to the observed variation in breast cancer risk for BRCA2 mutation carriers; those known to date have all been found through population-based genome-wide association studies (GWAS). To comprehensively identify breast cancer risk modifying loci for BRCA2 mutation carriers, we conducted a deep replication of an ongoing GWAS(More)
OBJECTIVE To estimate the expected magnitude of error produced by uncontrolled confounding from health behaviours in observational medical record-based studies evaluating effectiveness of screening colonoscopy. METHODS We used data from the prospective National Institutes of Health American Association of Retired Persons (NIH-AARP) Diet and Health Study(More)
Definitions and conceptualizations of confounding and selection bias have evolved over the past several decades. An important advance occurred with development of the concept of exchangeability. For example, if exchangeability holds, risks of disease in an unexposed group can be compared with risks in an exposed group to estimate causal effects. Another(More)
BACKGROUND An association between Jewish ethnicity and pancreatic cancer risk was suggested by analyses comparing pancreatic cancer mortality rates between Jews and non-Jews in New York in the 1950s. These analyses lacked information on potential confounding factors and the association between Jewish ethnicity and pancreatic cancer has not been examined in(More)
Factors suspected of causing certain chronic diseases and death are often associated with lower mortality among those with disease. For end-stage renal disease, examples include high cholesterol and homocysteine. Here, we consider obesity, thought to cause both end-stage renal disease and premature mortality, but which is associated with lower mortality(More)
PURPOSE Since oxidative stress involves a variety of cellular changes, no single biomarker can serve as a complete measure of this complex biological process. The analytic technique of structural equation modeling (SEM) provides a possible solution to this problem by modelling a latent (unobserved) variable constructed from the covariance of multiple(More)
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