The NFL outlined protocols Wednesday for the gradual reopening of team facilities amid the coronavirus pandemic.

Michigan coach Jim Harbaugh is urging the NFL and NCAA to amend their rules and provide flexibility to college football players who consider making the jump to the next level.

The NFL revealed its 2020 regular-season schedule Thursday, with the Kansas City Chiefs kicking off their Super Bowl title defense against the Houston Texans in Week 1.

OBJECTIVE

This study aimed to understand the longitudinal relationship between financial, psychosocial, and neighborhood social determinants and glycemic control (HbA_1c) in older adults with diabetes.

Indianapolis Colts quarterback Philip Rivers will become the head football coach at St. Michael Catholic High School, the school announced Friday.

TODAY Study Group
Jun 1, 2013; 36:1758-1764
TODAY Study

Peter J Garlick
Dec 1, 1991; 14:1189-1198
Diet and Diabetes

OBJECTIVE

To examine the association between manganese intake and the risk of type 2 diabetes in postmenopausal women and determine whether this association is mediated by circulating markers of inflammation.

OBJECTIVE

To examine whether low baseline diastolic blood pressure (DBP) modifies the effects of intensive systolic blood pressure (SBP) lowering on cardiovascular outcomes in type 2 diabetes mellitus (T2DM).

Over the last 40 years, climate change has been influencing where tropical cyclones form, according to a new study.

This Transatlantic Council on Migration Statement assesses the continuum of policies needed to disrupt illegal migration-related activities and addresses the conditions that make them possible. It examines the role of migration "bad actors"—human traffickers and unscrupulous employers, among them—who operate and profit in this environment, and considers how governments can deploy resources to discourage their actions.

This recipe features on Foodie Tuesday, a weekly segment on 774 Drive with Raf Epstein, 3.30PM, shared by Hetty McKinnon, founder of Surry Hills community kitchen Arthur Street Kitchen and author of 'Neighbourhood'.

Roger Dooley's book Brainfluence has just been released in an Italian translation.

The post Brainfluence Now Has An Italian Translation appeared first on Neuromarketing.

By Emily Reynolds. People are often required to adjust their behaviour to meet demands of apps, rather than technology being designed to meet our needs, researchers say.

Federal watchdogs find that Utah inflated its high school graduation rate in the last of a series of reports warning states not to make end runs around the rules for calculating graduation rates.

The NFL is indeed discussing the possibility of playing games on Saturdays in the event that college football doesn't proceed with a season from September through December. As one source with direct knowledge of the discussions tells PFT, however, the league's strong preference is for college football to happen, as scheduled. No college football season [more]

Women's flag football is set to be an official NAIA sport as soon as 2021.

American essays -- 21st century.

Celiac disease.

Depression, Mental -- Etiology.

Brunn : J.G. Trassler, 1821-1822.

Stuttgart : F. Enke, 1892.

Munchen : J.F. Lehmann, 1892.

Breslau : A. Gosohorsky, 1843.

Paris : J.-B. Baillière, 1877.

Edinburgh : Oliver and Boyd, 1888.

Paris : Rémont, 1815.

Neudamm : J. Neumann, 1890.

Spanking new stadiums in Los Angeles and Las Vegas unveiled in prime time. Business as usual, and you really can't blame the NFL for that. “The release of the NFL schedule is something our fans eagerly anticipate every year, as they look forward with hope and optimism to the season ahead,” Commissioner Roger Goodell said.

[Place of publication not identified] : [publisher not identified], [18--?]

Springfield, Virginia : National Technical Information Service, 1985.

Pac-12 student-athletes give shout-outs to their moms ahead of Mother's Day on May 10th, 2020 including UCLA's Michaela Onyenwere, Oregon's Sabrina Ionescu and Satou Sabally, Arizona's Aari McDonald, Cate Reese, and Lacie Hull, Stanford's Kiana Williams, USC's Endyia Rogers, and Aliyah Jeune, and Utah's Brynna Maxwell.

This paper develops deterministic upper and lower bounds on the influence measure in a network, more precisely, the expected number of nodes that a seed set can influence in the independent cascade model. In particular, our bounds exploit r-nonbacktracking walks and Fortuin-Kasteleyn-Ginibre (FKG) type inequalities, and are computed by message passing algorithms. Further, we provide parameterized versions of the bounds that control the trade-off between efficiency and accuracy. Finally, the tightness of the bounds is illustrated on various network models.

Weiping Zhang, Jiangli Wang, Fang Qian, Yu Chen.

Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 1, 35--50.

Abstract:
Longitudinal zero-inflated count data are widely encountered in many fields, while modeling the correlation between measurements for the same subject is more challenge due to the lack of suitable multivariate joint distributions. This paper studies a novel mean-correlation modeling approach for longitudinal zero-inflated regression model, solving both problems of specifying joint distribution and parsimoniously modeling correlations with no constraint. The joint distribution of zero-inflated discrete longitudinal responses is modeled by a copula model whose correlation parameters are innovatively represented in hyper-spherical coordinates. To overcome the computational intractability in maximizing the full likelihood function of the model, we further propose a computationally efficient pairwise likelihood approach. We then propose separated mean and correlation regression models to model these key quantities, such modeling approach can also handle irregularly and possibly subject-specific times points. The resulting estimators are shown to be consistent and asymptotically normal. Data example and simulations support the effectiveness of the proposed approach.

Luisa Rivas, Manuel Galea.

Source: Brazilian Journal of Probability and Statistics, Volume 33, Number 2, 402--424.

Abstract:
In this paper, we present a regression model where the response variable is a count data that follows a Waring distribution. The Waring regression model allows for analysis of phenomena where the Geometric regression model is inadequate, because the probability of success on each trial, $p$, is different for each individual and $p$ has an associated distribution. Estimation is performed by maximum likelihood, through the maximization of the $Q$-function using EM algorithm. Diagnostic measures are calculated for this model. To illustrate the results, an application to real data is presented. Some specific details are given in the Appendix of the paper.

Boyu Ren, Sergio Bacallado, Stefano Favaro, Tommi Vatanen, Curtis Huttenhower, Lorenzo Trippa.

Source: The Annals of Applied Statistics, Volume 14, Number 1, 494--517.

Abstract:
Detecting associations between microbial compositions and sample characteristics is one of the most important tasks in microbiome studies. Most of the existing methods apply univariate models to single microbial species separately, with adjustments for multiple hypothesis testing. We propose a Bayesian analysis for a generalized mixed effects linear model tailored to this application. The marginal prior on each microbial composition is a Dirichlet process, and dependence across compositions is induced through a linear combination of individual covariates, such as disease biomarkers or the subject’s age, and latent factors. The latent factors capture residual variability and their dimensionality is learned from the data in a fully Bayesian procedure. The proposed model is tested in data analyses and simulation studies with zero-inflated compositions. In these settings and within each sample, a large proportion of counts per microbial species are equal to zero. In our Bayesian model a priori the probability of compositions with absent microbial species is strictly positive. We propose an efficient algorithm to sample from the posterior and visualizations of model parameters which reveal associations between covariates and microbial compositions. We evaluate the proposed method in simulation studies, and then analyze a microbiome dataset for infants with type 1 diabetes which contains a large proportion of zeros in the sample-specific microbial compositions.

Paul J. Birrell, Lorenz Wernisch, Brian D. M. Tom, Leonhard Held, Gareth O. Roberts, Richard G. Pebody, Daniela De Angelis.

Source: The Annals of Applied Statistics, Volume 14, Number 1, 74--93.

Abstract:
A prompt public health response to a new epidemic relies on the ability to monitor and predict its evolution in real time as data accumulate. The 2009 A/H1N1 outbreak in the UK revealed pandemic data as noisy, contaminated, potentially biased and originating from multiple sources. This seriously challenges the capacity for real-time monitoring. Here, we assess the feasibility of real-time inference based on such data by constructing an analytic tool combining an age-stratified SEIR transmission model with various observation models describing the data generation mechanisms. As batches of data become available, a sequential Monte Carlo (SMC) algorithm is developed to synthesise multiple imperfect data streams, iterate epidemic inferences and assess model adequacy amidst a rapidly evolving epidemic environment, substantially reducing computation time in comparison to standard MCMC, to ensure timely delivery of real-time epidemic assessments. In application to simulated data designed to mimic the 2009 A/H1N1 epidemic, SMC is shown to have additional benefits in terms of assessing predictive performance and coping with parameter nonidentifiability.

David Corlin Marchand, Ioan Manolescu.

Source: Bernoulli, Volume 26, Number 3, 1665--1705.

Abstract:
We study randomly growing trees governed by the affine preferential attachment rule. Starting with a seed tree $S$, vertices are attached one by one, each linked by an edge to a random vertex of the current tree, chosen with a probability proportional to an affine function of its degree. This yields a one-parameter family of preferential attachment trees $(T_{n}^{S})_{ngeq |S|}$, of which the linear model is a particular case. Depending on the choice of the parameter, the power-laws governing the degrees in $T_{n}^{S}$ have different exponents. We study the problem of the asymptotic influence of the seed $S$ on the law of $T_{n}^{S}$. We show that, for any two distinct seeds $S$ and $S'$, the laws of $T_{n}^{S}$ and $T_{n}^{S'}$ remain at uniformly positive total-variation distance as $n$ increases. This is a continuation of Curien et al. ( J. Éc. Polytech. Math. 2 (2015) 1–34), which in turn was inspired by a conjecture of Bubeck et al. ( IEEE Trans. Netw. Sci. Eng. 2 (2015) 30–39). The technique developed here is more robust than previous ones and is likely to help in the study of more general attachment mechanisms.

Brian Neelon.

Source: Bayesian Analysis, Volume 14, Number 3, 849--875.

Abstract:
Motivated by a study examining spatiotemporal patterns in inpatient hospitalizations, we propose an efficient Bayesian approach for fitting zero-inflated negative binomial models. To facilitate posterior sampling, we introduce a set of latent variables that are represented as scale mixtures of normals, where the precision terms follow independent Pólya-Gamma distributions. Conditional on the latent variables, inference proceeds via straightforward Gibbs sampling. For fixed-effects models, our approach is comparable to existing methods. However, our model can accommodate more complex data structures, including multivariate and spatiotemporal data, settings in which current approaches often fail due to computational challenges. Using simulation studies, we highlight key features of the method and compare its performance to other estimation procedures. We apply the approach to a spatiotemporal analysis examining the number of annual inpatient admissions among United States veterans with type 2 diabetes.

Lei Liu, Ya-Chen Tina Shih, Robert L. Strawderman, Daowen Zhang, Bankole A. Johnson, Haitao Chai.

Source: Statistical Science, Volume 34, Number 2, 253--279.

Abstract:
Zero-inflated nonnegative continuous (or semicontinuous) data arise frequently in biomedical, economical, and ecological studies. Examples include substance abuse, medical costs, medical care utilization, biomarkers (e.g., CD4 cell counts, coronary artery calcium scores), single cell gene expression rates, and (relative) abundance of microbiome. Such data are often characterized by the presence of a large portion of zero values and positive continuous values that are skewed to the right and heteroscedastic. Both of these features suggest that no simple parametric distribution may be suitable for modeling such type of outcomes. In this paper, we review statistical methods for analyzing zero-inflated nonnegative outcome data. We will start with the cross-sectional setting, discussing ways to separate zero and positive values and introducing flexible models to characterize right skewness and heteroscedasticity in the positive values. We will then present models of correlated zero-inflated nonnegative continuous data, using random effects to tackle the correlation on repeated measures from the same subject and that across different parts of the model. We will also discuss expansion to related topics, for example, zero-inflated count and survival data, nonlinear covariate effects, and joint models of longitudinal zero-inflated nonnegative continuous data and survival. Finally, we will present applications to three real datasets (i.e., microbiome, medical costs, and alcohol drinking) to illustrate these methods. Example code will be provided to facilitate applications of these methods.

Zhengui Xia
Sep 1, 1996; 16:5425-5436
Articles

Italian translation of the BIS press release about the BIS Quarterly Review, September 2017

Paper by Mr Luiz Awazu Pereira da Silva, Deputy General Manager of the BIS, Enisse Kharroubi, Emanuel Kohlscheen and Benoît Mojon based on remarks at the University of Basel, 5 May 2019.