A nonparametric empirical Bayes framework for large-scale multiple testing

We propose a flexible and identifiable version of the two-groups model, motivated by hierarchical Bayes considerations, that features an empirical null and a semiparametric mixture model for the non-null cases. We use a computationally efficient predictive recursion marginal likelihood procedure to estimate the model parameters, even the nonparametric mixing distribution. This leads to a nonparametric empirical Bayes testing procedure, which we call PRtest, based on thresholding the estimated local false discovery rates. Simulations and real-data examples demonstrate that, compared to existing approaches, PRtest's careful handling of the non-null density can give a much better fit in the tails of the mixture distribution which, in turn, can lead to more realistic conclusions.Comment: 18 pages, 4 figures, 3 table

Coronal Thick Target Hard X Ray Emissions and Radio Emissions

Recently a distinctive class of hard X ray (HXR) sources located in the corona was found, which implies that the collisionally thick target model (CTTM) applies even to the corona. We investigated whether this idea can independently be verified by microwave radiations that have been known as the best companion to HXRs. The study is made for the GOES M2.3 class flare occurred on 2002 September 9 that were observed by the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) and the Owens Valley Solar Array (OVSA). Interpreting the observed energy dependent variation of HXR source size under the CTTM the coronal density should be as high as $5\times 10^{11}$ cm$^{-3}$ over the distance up to 12$"$. To explain the cut-off feature of microwave spectrum at 3 GHz, we however, need density no higher than $1\times 10^{11}$ cm$^{-3}$. Additional constraints need to be placed on temperature and magnetic field of the coronal source in order to reproduce the microwave spectrum as a whole. Firstly, a spectral feature called the Razin suppression requires the magnetic field in a range of 250--350 gauss along with high viewing angles around 75$^{\rm o}$. Secondly, to avoid excess fluxes at high frequencies due to the free-free emission that were not observed, we need a high temperature $\geq2\times 10^7$ K. These two microwave spectral features, Razzin suppression and free-free emissions, become more significant at regions of high thermal plasma density and are essential for validating and for determining additional parameters for the coronal HXR sources.Comment: APJ Letters, in pres

Interactions between empathy and resting heart rate in early adolescence predict violent behavior in late adolescence and early adulthood.

BackgroundAlthough resting heart rate (RHR) and empathy are independently and negatively associated with violent behavior, relatively little is known about the interplay between these psychophysiological and temperament-related risk factors.MethodsUsing a sample of 160 low-income, racially diverse men followed prospectively from infancy through early adulthood, this study examined whether RHR and empathy during early adolescence independently and interactively predict violent behavior and related correlates in late adolescence and early adulthood.ResultsControlling for child ethnicity, family income, and child antisocial behavior at age 12, empathy inversely predicted moral disengagement and juvenile petitions for violent crimes, while RHR was unrelated to all measures of violent behavior. Interactive effects were also evident such that among men with lower but not higher levels of RHR, lower empathy predicted increased violent behavior, as indexed by juvenile arrests for violent offenses, peer-reported violent behavior at age 17, self-reported moral disengagement at age 17, and self-reported violent behavior at age 20.ConclusionsImplications for prevention and intervention are considered. Specifically, targeting empathic skills among individuals at risk for violent behavior because of specific psychophysiological profiles may lead to more impactful interventions

The interaction between monoamine oxidase A and punitive discipline in the development of antisocial behavior: Mediation by maladaptive social information processing.

Previous studies demonstrate that boys' monoamine oxidase A (MAOA) genotype interacts with adverse rearing environments in early childhood, including punitive discipline, to predict later antisocial behavior. Yet the mechanisms by which MAOA and punitive parenting interact during childhood to amplify risk for antisocial behavior are not well understood. In the present study, hostile attributional bias and aggressive response generation during middle childhood, salient aspects of maladaptive social information processing, were tested as possible mediators of this relation in a sample of 187 low-income men followed prospectively from infancy into early adulthood. Given racial-ethnic variation in MAOA allele frequencies, analyses were conducted separately by race. In both African American and Caucasian men, those with the low-activity MAOA allele who experienced more punitive discipline at age 1.5 generated more aggressive responses to perceived threat at age 10 relative to men with the high-activity variant. In the African American subsample only, formal mediation analyses indicated a marginally significant indirect effect of maternal punitiveness on adult arrest records via aggressive response generation in middle childhood. The findings suggest that maladaptive social information processing may be an important mechanism underlying the association between MAOA × Parenting interactions and antisocial behavior in early adulthood. The present study extends previous work in the field by demonstrating that MAOA and harsh parenting assessed in early childhood interact to not only predict antisocial behavior in early adulthood, but also predict social information processing, a well-established social-cognitive correlate of antisocial behavior