Reduced Bayesian Hierarchical Models: Estimating Health Effects of Simultaneous Exposure to Multiple Pollutants

Quantifying the health effects associated with simultaneous exposure to many air pollutants is now a research priority of the US EPA. Bayesian hierarchical models (BHM) have been extensively used in multisite time series studies of air pollution and health to estimate health effects of a single pollutant adjusted for potential confounding of other pollutants and other time-varying factors. However, when the scientific goal is to estimate the impacts of many pollutants jointly, a straightforward application of BHM is challenged by the need to specify a random-effect distribution on a high-dimensional vector of nuisance parameters, which often do not have an easy interpretation. In this paper we introduce a new BHM formulation, which we call "reduced BHM", aimed at analyzing clustered data sets in the presence of a large number of random effects that are not of primary scientific interest. At the first stage of the reduced BHM, we calculate the integrated likelihood of the parameter of interest (e.g. excess number of deaths attributed to simultaneous exposure to high levels of many pollutants). At the second stage, we specify a flexible random-effect distribution directly on the parameter of interest. The reduced BHM overcomes many of the challenges in the specification and implementation of full BHM in the context of a large number of nuisance parameters. In simulation studies we show that the reduced BHM performs comparably to the full BHM in many scenarios, and even performs better in some cases. Methods are applied to estimate location-specific and overall relative risks of cardiovascular hospital admissions associated with simultaneous exposure to elevated levels of particulate matter and ozone in 51 US counties during the period 1999-2005.

ON MARGINALIZED MULTILEVEL MODELS AND THEIR COMPUTATION

Clustered data analysis is characterized by the need to describe both systematic variation in a mean model and cluster-dependent random variation in an association model. Marginalized multilevel models embrace the robustness and interpretations of a marginal mean model, while retaining the likelihood inference capabilities and flexible dependence structures of a conditional association model. Although there has been increasing recognition of the attractiveness of marginalized multilevel models, there has been a gap in their practical application arising from a lack of readily available estimation procedures. We extend the marginalized multilevel model to allow for nonlinear functions in both the mean and association aspects. We then formulate marginal models through conditional specifications to facilitate estimation with mixed model computational solutions already in place. We illustrate this approach on a cerebrovascular deficiency crossover trial.

RANDOM EFFECTS MODELS IN A META-ANALYSIS OF THE ACCURACY OF DIAGNOSTIC TESTS WITHIN A GOLD STANDARD IN THE PRESENCE OF MISSING DATA

In evaluating the accuracy of diagnosis tests, it is common to apply two imperfect tests jointly or sequentially to a study population. In a recent meta-analysis of the accuracy of microsatellite instability testing (MSI) and traditional mutation analysis (MUT) in predicting germline mutations of the mismatch repair (MMR) genes, a Bayesian approach (Chen, Watson, and Parmigiani 2005) was proposed to handle missing data resulting from partial testing and the lack of a gold standard. In this paper, we demonstrate an improved estimation of the sensitivities and specificities of MSI and MUT by using a nonlinear mixed model and a Bayesian hierarchical model, both of which account for the heterogeneity across studies through study-specific random effects. The methods can be used to estimate the accuracy of two imperfect diagnostic tests in other meta-analyses when the prevalence of disease, the sensitivities and/or the specificities of diagnostic tests are heterogeneous among studies. Furthermore, simulation studies have demonstrated the importance of carefully selecting appropriate random effects on the estimation of diagnostic accuracy measurements in this scenario.

Multilevel Latent Class Models with Dirichlet Mixing Distribution

Latent class analysis (LCA) and latent class regression (LCR) are widely used for modeling multivariate categorical outcomes in social sciences and biomedical studies. Standard analyses assume data of different respondents to be mutually independent, excluding application of the methods to familial and other designs in which participants are clustered. In this paper, we develop multilevel latent class model, in which subpopulation mixing probabilities are treated as random effects that vary among clusters according to a common Dirichlet distribution. We apply the Expectation-Maximization (EM) algorithm for model fitting by maximum likelihood (ML). This approach works well, but is computationally intensive when either the number of classes or the cluster size is large. We propose a maximum pairwise likelihood (MPL) approach via a modified EM algorithm for this case. We also show that a simple latent class analysis, combined with robust standard errors, provides another consistent, robust, but less efficient inferential procedure. Simulation studies suggest that the three methods work well in finite samples, and that the MPL estimates often enjoy comparable precision as the ML estimates. We apply our methods to the analysis of comorbid symptoms in the Obsessive Compulsive Disorder study. Our models' random effects structure has more straightforward interpretation than those of competing methods, thus should usefully augment tools available for latent class analysis of multilevel data.

Transformer modeling ATP : internal faults & high-frequency discretization

Power transformers are key components of the power grid and are also one of the most subjected to a variety of power system transients. The failure of a large transformer can cause severe monetary losses to a utility, thus adequate protection schemes are of great importance to avoid transformer damage and maximize the continuity of service. Computer modeling can be used as an efficient tool to improve the reliability of a transformer protective relay application. Unfortunately, transformer models presently available in commercial software lack completeness in the representation of several aspects such as internal winding faults, which is a common cause of transformer failure. It is also important to adequately represent the transformer at frequencies higher than the power frequency for a more accurate simulation of switching transients since these are a well known cause for the unwanted tripping of protective relays. This work develops new capabilities for the Hybrid Transformer Model (XFMR) implemented in ATPDraw to allow the representation of internal winding faults and slow-front transients up to 10 kHz. The new model can be developed using any of two sources of information: 1) test report data and 2) design data. When only test-report data is available, a higher-order leakage inductance matrix is created from standard measurements. If design information is available, a Finite Element Model is created to calculate the leakage parameters for the higher-order model. An analytical model is also implemented as an alternative to FEM modeling. Measurements on 15-kVA 240?/208Y V and 500-kVA 11430Y/235Y V distribution transformers were performed to validate the model. A transformer model that is valid for simulations for frequencies above the power frequency was developed after continuing the division of windings into multiple sections and including a higher-order capacitance matrix. Frequency-scan laboratory measurements were used to benchmark the simulations. Finally, a stability analysis of the higher-order model was made by analyzing the trapezoidal rule for numerical integration as used in ATP. Numerical damping was also added to suppress oscillations locally when discontinuities occurred in the solution. A maximum error magnitude of 7.84% was encountered in the simulated currents for different turn-to-ground and turn-to-turn faults. The FEM approach provided the most accurate means to determine the leakage parameters for the ATP model. The higher-order model was found to reproduce the short-circuit impedance acceptably up to about 10 kHz and the behavior at the first anti-resonant frequency was better matched with the measurements.

Handbook of LHC Higgs Cross Sections: 3. Higgs Properties. Report of the LHC Higgs Cross Section Working Group

This Report summarizes the results of the activities in 2012 and the first half of 2013 of the LHC Higgs Cross Section Working Group. The main goal of the working group was to present the state of the art of Higgs Physics at the LHC, integrating all new results that have appeared in the last few years. This report follows the first working group report Handbook of LHC Higgs Cross Sections: 1. Inclusive Observables (CERN-2011-002) and the second working group report Handbook of LHC Higgs Cross Sections: 2. Differential Distributions (CERN-2012-002). After the discovery of a Higgs boson at the LHC in mid-2012 this report focuses on refined prediction of Standard Model (SM) Higgs phenomenology around the experimentally observed value of 125-126 GeV, refined predictions for heavy SM-like Higgs bosons as well as predictions in the Minimal Supersymmetric Standard Model and first steps to go beyond these models. The other main focus is on the extraction of the characteristics and properties of the newly discovered particle such as couplings to SM particles, spin and CP-quantum numbers etc.

Theoretical models of planetary system formation: mass vs. semi-major axis

Context. Planet formation models have been developed during the past years to try to reproduce what has been observed of both the solar system and the extrasolar planets. Some of these models have partially succeeded, but they focus on massive planets and, for the sake of simplicity, exclude planets belonging to planetary systems. However, more and more planets are now found in planetary systems. This tendency, which is a result of radial velocity, transit, and direct imaging surveys, seems to be even more pronounced for low-mass planets. These new observations require improving planet formation models, including new physics, and considering the formation of systems. Aims: In a recent series of papers, we have presented some improvements in the physics of our models, focussing in particular on the internal structure of forming planets, and on the computation of the excitation state of planetesimals and their resulting accretion rate. In this paper, we focus on the concurrent effect of the formation of more than one planet in the same protoplanetary disc and show the effect, in terms of architecture and composition of this multiplicity. Methods: We used an N-body calculation including collision detection to compute the orbital evolution of a planetary system. Moreover, we describe the effect of competition for accretion of gas and solids, as well as the effect of gravitational interactions between planets. Results: We show that the masses and semi-major axes of planets are modified by both the effect of competition and gravitational interactions. We also present the effect of the assumed number of forming planets in the same system (a free parameter of the model), as well as the effect of the inclination and eccentricity damping. We find that the fraction of ejected planets increases from nearly 0 to 8% as we change the number of embryos we seed the system with from 2 to 20 planetary embryos. Moreover, our calculations show that, when considering planets more massive than ~5 M⊕, simulations with 10 or 20 planetary embryos statistically give the same results in terms of mass function and period distribution.

EFFECTS OF INFORMATION DISPLAY ON THE CONSTRUCTION OF CLINICIAN MENTAL MODELS

Objective: To determine how a clinician’s background knowledge, their tasks, and displays of information interact to affect the clinician’s mental model. Design: Repeated Measure Nested Experimental Design Population, Sample, Setting: Populations were gastrointestinal/internal medicine physicians and nurses within the greater Houston area. A purposeful sample of 24 physicians and 24 nurses were studied in 2003. Methods: Subjects were randomized to two different displays of two different mock medical records; one that contained highlighted patient information and one that contained non-highlighted patient information. They were asked to read and summarize their understanding of the patients aloud. Propositional analysis was used to understand their comprehension of the patients. Findings: Different mental models were found between physicians and nurses given the same display of information. The information they shared was very minor compared to the variance in their mental models. There was additionally more variance within the nursing mental models than the physician mental models given different displays of the same information. Statistically, there was no interaction effect between the display of information and clinician type. Only clinician type could account for the differences in the clinician comprehension and thus their mental models of the cases. Conclusion: The factors that may explain the variance within and between the clinician models are clinician type, and only in the nursing group, the use of highlighting.

THE INTERACTION BETWEEN INTERNAL AND EXTERNAL INFORMATION ON RELATIONAL DATA SEARCH

People often use tools to search for information. In order to improve the quality of an information search, it is important to understand how internal information, which is stored in user’s mind, and external information, represented by the interface of tools interact with each other. How information is distributed between internal and external representations significantly affects information search performance. However, few studies have examined the relationship between types of interface and types of search task in the context of information search. For a distributed information search task, how data are distributed, represented, and formatted significantly affects the user search performance in terms of response time and accuracy. Guided by UFuRT (User, Function, Representation, Task), a human-centered process, I propose a search model, task taxonomy. The model defines its relationship with other existing information models. The taxonomy clarifies the legitimate operations for each type of search task of relation data. Based on the model and taxonomy, I have also developed prototypes of interface for the search tasks of relational data. These prototypes were used for experiments. The experiments described in this study are of a within-subject design with a sample of 24 participants recruited from the graduate schools located in the Texas Medical Center. Participants performed one-dimensional nominal search tasks over nominal, ordinal, and ratio displays, and searched one-dimensional nominal, ordinal, interval, and ratio tasks over table and graph displays. Participants also performed the same task and display combination for twodimensional searches. Distributed cognition theory has been adopted as a theoretical framework for analyzing and predicting the search performance of relational data. It has been shown that the representation dimensions and data scales, as well as the search task types, are main factors in determining search efficiency and effectiveness. In particular, the more external representations used, the better search task performance, and the results suggest the ideal search performance occurs when the question type and corresponding data scale representation match. The implications of the study lie in contributing to the effective design of search interface for relational data, especially laboratory results, which are often used in healthcare activities.

From school to work: A comprehensive model of work-related motivation in the transition to working life.

Motivation is a core concept to understand work related outcomes and vocational pursuits. However, existing research mostly focused on specific aspects of motivation, such as goals or self-efficacy beliefs, while falling short of adequately addressing more complex and integrative notions of motivation. Advancing the current state of research, we draw from Motivational Systems Theory and a model of proactive motivation to propose a comprehensive model of work-related motivation. Specifically, we define motivation as a system of mutually related factors consisting of goals, emotions, and personal agency beliefs, comprised by capability beliefs and context evaluations. Adapting this model of motivation to the school-to-work transition, we postulate that this motivational system is affected by different social, personal, and environmental variables, for example social support, the presence of role-models, personality traits, and scholastic achievement. We further expect that students with more autonomous work-related goals, expectations of more positive emotional experiences in their future working life, fewer perceived barriers to their career development, and higher work-related self-efficacy beliefs would be more successful in their transition from school to work. We also propose that goal-directed engagement acts as a partial mediator in the relationship between motivation and a successful transition. Finally, we hypothesize that work-related motivation while in school will have meaningful effects on positive outcomes while in vocational training, as represented by more work engagement, higher career commitment, job satisfaction, and lower intentions to quit training. In sum, we advance the point that the adaptation of a broader concept of work-related motivation in the school-to-work transition would result in more powerful predictions of success in this transition and would enhance scientific research and interventions in career development and counselling practice.

Three-dimensional printing creates models for surgical planning of aortic valve replacement after previous coronary bypass grafting.

PURPOSE Resternotomy for aortic valve replacement in patients with previous coronary artery bypass grafting and an internal mammary artery graft may be a surgical problem. Thus, we are exploring the effect of using rapid prototyping techniques for surgical planning and intraoperative orientation during aortic valve replacement after previous coronary artery bypass grafting (CABG). DESCRIPTION As a proof of concept, we studied a patient who had undergone CABG 5 years earlier. At that time the patient received a left internal mammary artery graft to the left anterior descending artery and a venous graft to the right coronary artery. Now the patient required aortic valve replacement due to symptomatic aortic valve stenosis. The left internal mammary artery bypass and the right coronary artery bypass were patent and showed good flow in the angiography. The patient was examined by 128-slice computed tomography. The image data were visualized and reconstructed. Afterwards, a replica showing the anatomic structures was fabricated using a rapid prototyping machine. EVALUATION Using data derived from 128-slice computed tomography angiography linked to proprietary software, we were able to create three-dimensional reconstructions of the vascular anatomy after the previous CABG. The models were sterilized and taken to the operating theatre for orientation during the surgical procedure. CONCLUSIONS Stereolithographic replicas are helpful for choosing treatment strategies in surgical planning and for intraoperative orientation during reoperations of patients with previous CABG.

Efficacy of a dilemma-focused intervention for unipolar depression: study protocol for a multicenter randomized controlled trial

BACKGROUND: Depression is one of the more severe and serious health problems because of its morbidity, disabling effects and for its societal and economic burden. Despite the variety of existing pharmacological and psychological treatments, most of the cases evolve with only partial remission, relapse and recurrence.Cognitive models have contributed significantly to the understanding of unipolar depression and its psychological treatment. However, success is only partial and many authors affirm the need to improve those models and also the treatment programs derived from them. One of the issues that requires further elaboration is the difficulty these patients experience in responding to treatment and in maintaining therapeutic gains across time without relapse or recurrence. Our research group has been working on the notion of cognitive conflict viewed as personal dilemmas according to personal construct theory. We use a novel method for identifying those conflicts using the repertory grid technique (RGT). Preliminary results with depressive patients show that about 90% of them have one or more of those conflicts. This fact might explain the blockage and the difficult progress of these patients, especially the more severe and/or chronic. These results justify the need for specific interventions focused on the resolution of these internal conflicts. This study aims to empirically test the hypothesis that an intervention focused on the dilemma(s) specifically detected for each patient will enhance the efficacy of cognitive behavioral therapy (CBT) for depression. DESIGN: A therapy manual for a dilemma-focused intervention will be tested using a randomized clinical trial by comparing the outcome of two treatment conditions: combined group CBT (eight, 2-hour weekly sessions) plus individual dilemma-focused therapy (eight, 1-hour weekly sessions) and CBT alone (eight, 2-hour group weekly sessions plus eight, 1-hour individual weekly sessions). METHOD: Participants are patients aged over 18 years meeting diagnostic criteria for major depressive disorder or dysthymic disorder, with a score of 19 or above on the Beck depression inventory, second edition (BDI-II) and presenting at least one cognitive conflict (implicative dilemma or dilemmatic construct) as assessed using the RGT. The BDI-II is the primary outcome measure, collected at baseline, at the end of therapy, and at 3- and 12-month follow-up; other secondary measures are also used. DISCUSSION: We expect that adding a dilemma-focused intervention to CBT will increase the efficacy of one of the more prestigious therapies for depression, thus resulting in a significant contribution to the psychological treatment of depression. TRIAL REGISTRATION: ISRCTN92443999; ClinicalTrials.gov Identifier: NCT01542957.

Keeping Promises : Implementing the UNESCO Convention on Cultural Diversity into EU's Internal Policies

Irrespective of the diverse stances taken on the UNESCO Convention’s bearing in the external relations context, since its wording is fairly open-ended, it is clear to all observers that the Convention’s impact will largely depend on how it is implemented. The discussion on the domestic implementation of the Convention, both in the political and in the academic discourses, is only just emerging. The implementation model of the EU and its Member States could set an important example for the international community and for the other State Parties that ratified the UNESCO Convention, as the EU and the Member States acting individually, played a critical role in the approval of the Convention, and in the longer process of promoting cultural concerns on the international scene. Against this background, it is the objective of the present article to analyse in how far EU’s internal policies are taking account of the spirit and letter of the UNESCO Convention on Cultural Diversity, to critically assess these policies and make some recommendations for adjustment.

Analytical Models of Exoplanetary Atmospheres. II. Radiative Transfer via the Two-Stream Approximation

We present a comprehensive analytical study of radiative transfer using the method of moments and include the effects of non-isotropic scattering in the coherent limit. Within this unified formalism, we derive the governing equations and solutions describing two-stream radiative transfer (which approximates the passage of radiation as a pair of outgoing and incoming fluxes), flux-limited diffusion (which describes radiative transfer in the deep interior) and solutions for the temperature-pressure profiles. Generally, the problem is mathematically under-determined unless a set of closures (Eddington coefficients) is specified. We demonstrate that the hemispheric (or hemi-isotropic) closure naturally derives from the radiative transfer equation if energy conservation is obeyed, while the Eddington closure produces spurious enhancements of both reflected light and thermal emission. We concoct recipes for implementing two-stream radiative transfer in stand-alone numerical calculations and general circulation models. We use our two-stream solutions to construct toy models of the runaway greenhouse effect. We present a new solution for temperature-pressure profiles with a non-constant optical opacity and elucidate the effects of non-isotropic scattering in the optical and infrared. We derive generalized expressions for the spherical and Bond albedos and the photon deposition depth. We demonstrate that the value of the optical depth corresponding to the photosphere is not always 2/3 (Milne's solution) and depends on a combination of stellar irradiation, internal heat and the properties of scattering both in optical and infrared. Finally, we derive generalized expressions for the total, net, outgoing and incoming fluxes in the convective regime.

Elucidating the internal structure of psychophysical timing performance in the sub-second and second range by utilizing confirmatory factor analysis

The most influential theoretical account in time psychophysics assumes the existence of a unitary internal clock based on neural counting. The distinct timing hypothesis, on the other hand, suggests an automatic timing mechanism for processing of durations in the sub-second range and a cognitively controlled timing mechanism for processing of durations in the range of seconds. Although several psychophysical approaches can be applied for identifying the internal structure of interval timing in the second and sub-second range, the existing data provide a puzzling picture of rather inconsistent results. In the present chapter, we introduce confirmatory factor analysis (CFA) to further elucidate the internal structure of interval timing performance in the sub-second and second range. More specifically, we investigated whether CFA would rather support the notion of a unitary timing mechanism or of distinct timing mechanisms underlying interval timing in the sub-second and second range, respectively. The assumption of two distinct timing mechanisms which are completely independent of each other was not supported by our data. The model assuming a unitary timing mechanism underlying interval timing in both the sub-second and second range fitted the empirical data much better. Eventually, we also tested a third model assuming two distinct, but functionally related mechanisms. The correlation between the two latent variables representing the hypothesized timing mechanisms was rather high and comparison of fit indices indicated that the assumption of two associated timing mechanisms described the observed data better than only one latent variable. Models are discussed in the light of the existing psychophysical and neurophysiological data.