Gap bootstrap methods for massive data sets with an application to transportation engineering

In this paper we describe two bootstrap methods for massive data sets. Naive applications of common resampling methodology are often impractical for massive data sets due to computational burden and due to complex patterns of inhomogeneity. In contrast, the proposed methods exploit certain structural properties of a large class of massive data sets to break up the original problem into a set of simpler subproblems, solve each subproblem separately where the data exhibit approximate uniformity and where computational complexity can be reduced to a manageable level, and then combine the results through certain analytical considerations. The validity of the proposed methods is proved and their finite sample properties are studied through a moderately large simulation study. The methodology is illustrated with a real data example from Transportation Engineering, which motivated the development of the proposed methods.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS587 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Size effect in the ionization energy of PAH clusters

We report the first experimental measurement of the near-threshold photo-ionization spectra of polycyclic aromatic hydrocarbon clusters made of pyrene C16H10 and coronene C24H12, obtained using imaging photoelectron photoion coincidence spectrometry with a VUV synchrotron beamline. The experimental results of the ionization energy are confronted to calculated ones obtained from simulations using dedicated electronic structure treatment for large ionized molecular clusters. Experiment and theory consistently find a decrease of the ionization energy with cluster size. The inclusion of temperature effects in the simulations leads to a lowering of this energy and to a quantitative agreement with the experiment. In the case of pyrene, both theory and experiment show a discontinuity in the IE trend for the hexamer

Interpretation of the Individual Effect Under Treatment Spillover

Some interventions are intended to benefit both individuals and the groups to which they belong. When a treatment given to one person exerts a causal effect on others, the treatment is said to exhibit spillover, dissemination, or interference. However, defining meaningful causal effects under spillover can be challenging. In this commentary, we discuss the meaning of the “individual effect,” a quantity proposed to summarize the effect of treatment on the person who receives it, when spillover may be present

Assessing Individual and Disseminated Effects in Network-Randomized Studies

Implementation trials often involve clustering via risk networks, where only some participants directly received the intervention. The individual effect is that among directly treated persons beyond being in an intervention network; the disseminated effect is that among persons engaged with those directly treated. We employ a causal inference framework and discuss assumptions and estimators for individual and disseminated effects and apply them to HIV Prevention Trials Network 037. HIV Prevention Trials Network 037 was a Phase III, network-level, randomized controlled HIV prevention trial conducted in the US and Thailand from 2002 to 2006 that recruited persons who injected drugs, who received either intervention or control, and their risk network members, who received no direct intervention. Combining individual and disseminated, a 35% composite rate reduction was observed in the adjusted model (95% confidence interval = 0.47, 0.90). Methodology is now available to estimate the full set of these effects enhancing knowledge gained from network-randomized trials. Although the overall effect gains validity from network randomization, we show that it will, in general, be less than the composite effect. Additionally, if only index participants benefit from the intervention, as the network size increases, the overall effect tends to the null, an unfortunate and misleading conclusion

Impact of early initiation versus national standard of care of antiretroviral therapy in Swaziland's public sector health system : study protocol for a stepped-wedge randomized trial

Background: There is robust clinical evidence to support offering early access to antiretroviral treatment (ART) to all HIV-positive individuals, irrespective of disease stage, to both improve patient health outcomes and reduce HIV incidence. However, as the global treatment guidelines shift to meet this evidence, it is still largely unknown if early access to ART for all (also referred to as "treatment as prevention" or " universal test and treat") is a feasible intervention in the resource-limited countries where this approach could have the biggest impact on the course of the HIV epidemics. The MaxART Early Access to ART for All (EAAA) implementation study was designed to determine the feasibility, acceptability, clinical outcomes, affordability, and scalability of offering early antiretroviral treatment to all HIV-positive individuals in Swaziland's public sector health system. Methods: This is a three-year stepped-wedge randomized design with open enrollment for all adults aged 18 years and older across 14 government-managed health facilities in Swaziland's Hhohho Region. Primary endpoints are retention and viral suppression. Secondary endpoints include ART initiation, adherence, drug resistance, tuberculosis, HIV disease progression, patient satisfaction, and cost per patient per year. Sites are grouped to transition two at a time from the control (standard of care) to intervention (EAAA) stage at each four-month step. This design will result in approximately one half of the total observation time to accrue in the intervention arm and the other half in the control arm. Our estimated enrolment number, which is supported by conservative power calculations, is 4501 patients over the course of the 36-month study period. A multidisciplinary, mixed-methods approach will be adopted to supplement the randomized controlled trial and meet the study aims. Additional study components include implementation science, social science, economic evaluation, and predictive HIV incidence modeling. Discussion: A stepped-wedge randomized design is a causally strong and robust approach to determine if providing antiretroviral treatment for all HIV-positive individuals is a feasible intervention in a resource-limited, public sector health system. We expect our study results to contribute to health policy decisions related to the HIV response in Swaziland and other countries in sub-Saharan Africa

Make Research Data Public? -- Not Always so Simple: A Dialogue for Statisticians and Science Editors

Putting data into the public domain is not the same thing as making those data accessible for intelligent analysis. A distinguished group of editors and experts who were already engaged in one way or another with the issues inherent in making research data public came together with statisticians to initiate a dialogue about policies and practicalities of requiring published research to be accompanied by publication of the research data. This dialogue carried beyond the broad issues of the advisability, the intellectual integrity, the scientific exigencies to the relevance of these issues to statistics as a discipline and the relevance of statistics, from inference to modeling to data exploration, to science and social science policies on these issues.Comment: Published in at http://dx.doi.org/10.1214/10-STS320 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org