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Genetic susceptibility to antisocial behavior may increase fetal sensitivity to prenatal exposure to cigarette smoke. Testing putative gene x exposure mechanisms requires precise measurement of exposure and outcomes. We tested whether a functional polymorphism in the gene encoding the enzyme monoamine oxidase A (MAOA) interacts with exposure to predict(More)
Concerns over bioterrorism and emerging diseases have led to the widespread use of epidemic models for evaluating public health strategies. Partly because epidemic models often capture the dynamics of prior epidemics remarkably well, little attention has been paid to how uncertainty in parameter estimates might affect model predictions. To understand such(More)
Current meta-analytic methods for diagnostic test accuracy are generally applicable to a selection of studies reporting only estimates of sensitivity and specificity, or at most, to studies whose results are reported using an equal number of ordered categories. In this article, we propose a new meta-analytic method to evaluate test accuracy and arrive at a(More)
OBJECTIVE Nonconvulsive seizures (NCSz) are frequent following acute brain injury and have been implicated as a cause of secondary brain injury, but mechanisms that cause NCSz are controversial. Proinflammatory states are common after many brain injuries, and inflammation-mediated changes in blood-brain barrier permeability have been experimentally linked(More)
INTRODUCTION The effects of tobacco exposure are typically examined by comparing groups based on a cut-score of self-reported number of cigarettes or bioassays collected in cross-sectional studies. This study introduces a new fuzzy clustering method that facilitates detection of subtle exposure effects by objectively deriving subgroups from modeling(More)
Thanks to advances in MCMC methodology, Bayesian curve estimation has become an increasingly popular subject both in practice and in theoretical research. Prior specification for curves is a more challenging task than for scalar or multivariate parameters. Besides using fully parametric curves, common strategies include using a stochastic process or(More)
The multiresolution estimator, developed originally in engineering applications as a wavelet-based method for density estimation, has been recently extended and adapted for estimation of hazard functions (Bouman et al. 2005, 2007). Using the multiresolution hazard (MRH) estimator in the Bayesian framework, we are able to incorporate any a priori desired(More)
Studies of effects of prenatal exposure to cigarettes frequently acquire both self-report and biological assays of maternal smoking. However, little attention has been paid to methods for combining information from both sources to enhance the precision of exposure measurement. This paper analyzes the relationship between the two commonly used measures of(More)
In this paper we use Google Flu Trends data together with a sequential surveillance model based on the state-space methodology, to track the evolution of an epidemic process over time. We embed a classical mathematical epidemiology model (a susceptible-exposed-infectedrecovered (SEIR) model) within the state-space framework, thereby allowing the SEIR(More)