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Introduction Prevalence is an indicator of primary interest in public health because it measures the burden of cancer in a population and on the health care system. Prevalence is defined as the number or percent of people alive on a certain date in a population who previously had a diagnosis of the disease. It includes new (incidence) and pre-existing cases(More)
Few studies have determined whether carotid artery intima-media thickness (IMT) is associated prospectively with risk of first ischemic stroke. In the Atherosclerosis Risk in Communities Study, carotid IMT, an index of generalized atherosclerosis, was defined as the mean of IMT measured by B-mode ultrasonography at six sites of the carotid arteries. The(More)
BACKGROUND Population-based cancer registry data from the Surveillance, Epidemiology, and End Results (SEER) Program at the National Cancer Institute (NCI) are mainly based on medical records and administrative information. Individual-level socioeconomic data are not routinely reported by cancer registries in the United States because they are not available(More)
Trends in incidence or mortality rates over a specified time interval are usually described by the conventional annual per cent change (cAPC), under the assumption of a constant rate of change. When this assumption does not hold over the entire time interval, the trend may be characterized using the annual per cent changes from segmented analysis (sAPCs).(More)
OBJECTIVES In this population-based cohort study, we assessed baseline risk factors for homelessness, including the role of service in the Iraq or Afghanistan conflicts, among a large cohort of recent veterans. METHODS Data for this study came from administrative records for 310,685 veterans who separated from active military duty from July 1, 2005, to(More)
We propose a new Poisson method to estimate the variance for prevalence estimates obtained by the counting method described by Gail et al. (1999, Biometrics 55, 1137-1144) and to construct a confidence interval for the prevalence. We evaluate both the Poisson procedure and the procedure based on the bootstrap proposed by Gail et al. in simulated samples(More)
BACKGROUND Epidemiologic research into cancer and subsequent decision making to reduce the cancer burden in the population are dependent on the quality of available data. The more reliable the data, the more confident we can be that the decisions made would have the desired effect in the population. The North American Association of Central Cancer(More)
Marginal models for multivariate failure time data with generalized dependence structure. (Under the joint direction of Drs. ABSTRACT In epidemiologic studies, there is often more than one outcome measured on the same subject. Multiple failures from the same individual induce multivariate failure time data involving within-subject dependence. Furthermore,(More)
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