Browsing by Author "Murphy, Robert"
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Item Open Access Bayesian network-response regression.(Bioinformatics, 2017-01-06) Wang, Lu; Durante, Daniele; Jung, Rex E; Dunson, David BMotivation: There is increasing interest in learning how human brain networks vary as a function of a continuous trait, but flexible and efficient procedures to accomplish this goal are limited. We develop a Bayesian semiparametric model, which combines low-rank factorizations and flexible Gaussian process priors to learn changes in the conditional expectation of a network-valued random variable across the values of a continuous predictor, while including subject-specific random effects. Results: The formulation leads to a general framework for inference on changes in brain network structures across human traits, facilitating borrowing of information and coherently characterizing uncertainty. We provide an efficient Gibbs sampler for posterior computation along with simple procedures for inference, prediction and goodness-of-fit assessments. The model is applied to learn how human brain networks vary across individuals with different intelligence scores. Results provide interesting insights on the association between intelligence and brain connectivity, while demonstrating good predictive performance. Availability and Implementation: Source code implemented in R and data are available at https://github.com/wangronglu/BNRR. Contact: rl.wang@duke.edu. Supplementary information: Supplementary data are available at Bioinformatics online.Item Open Access Toward Population Impact from Home Visiting.(Zero Three, 2013-01-01) Dodge, Kenneth A; Goodman, W Benjamin; Murphy, Robert; O'Donnell, Karen; Sato, JeannineAlthough some home-visiting programs have proven effective with the families they serve, no program has yet demonstrated an impact at the population level. We describe the Durham Connects (DC) initiative, which aims to achieve population impact by coalescing community agencies to serve early-intervention goals through a Preventive System Of Care and by delivering a universal, short-term, postnatal nurse home-visiting program. The home-visitor delivers brief intervention, assesses family needs in 12 domains, and connects the family with community resources to address individualized family needs. Evaluation of DC occurred through a population randomized controlled trial of all 4,777 births in Durham, NC, over an 18-month period. DC was implemented with high penetration and high fidelity. Impact evaluation indicated that by age 6 months, DC infants had 18 percent fewer emergency room visits and 80 percent fewer overnights in the hospital than did control families. We conclude that population impact is achievable if a program attends to challenges of community partnership, universal reach and assessment, rigorous evaluation, and models for sustaining funding.