Xiaoqin Wang, Li Yin.

Source: The Annals of Statistics, Volume 48, Number 1, 138--160.

Abstract:
In sequential causal inference, two types of causal effects are of practical interest, namely, the causal effect of the treatment regime (called the sequential causal effect) and the blip effect of treatment on the potential outcome after the last treatment. The well-known $G$-formula expresses these causal effects in terms of the standard parameters. In this article, we obtain a new $G$-formula that expresses these causal effects in terms of the point observable effects of treatments similar to treatment in the framework of single-point causal inference. Based on the new $G$-formula, we estimate these causal effects by maximum likelihood via point observable effects with methods extended from single-point causal inference. We are able to increase precision of the estimation without introducing biases by an unsaturated model imposing constraints on the point observable effects. We are also able to reduce the number of point observable effects in the estimation by treatment assignment conditions.

Aaditya K. Ramdas, Rina F. Barber, Martin J. Wainwright, Michael I. Jordan.

Source: The Annals of Statistics, Volume 47, Number 5, 2790--2821.

Abstract:
There is a significant literature on methods for incorporating knowledge into multiple testing procedures so as to improve their power and precision. Some common forms of prior knowledge include (a) beliefs about which hypotheses are null, modeled by nonuniform prior weights; (b) differing importances of hypotheses, modeled by differing penalties for false discoveries; (c) multiple arbitrary partitions of the hypotheses into (possibly overlapping) groups and (d) knowledge of independence, positive or arbitrary dependence between hypotheses or groups, suggesting the use of more aggressive or conservative procedures. We present a unified algorithmic framework called p-filter for global null testing and false discovery rate (FDR) control that allows the scientist to incorporate all four types of prior knowledge (a)–(d) simultaneously, recovering a variety of known algorithms as special cases.

Chengchun Shi, Rui Song, Wenbin Lu.

Source: The Annals of Statistics, Volume 47, Number 4, 2348--2377.

Abstract:
Precision medicine is an emerging medical paradigm that focuses on finding the most effective treatment strategy tailored for individual patients. In the literature, most of the existing works focused on estimating the optimal treatment regime. However, there has been less attention devoted to hypothesis testing regarding the optimal treatment regime. In this paper, we first introduce the notion of conditional qualitative treatment effects (CQTE) of a set of variables given another set of variables and provide a class of equivalent representations for the null hypothesis of no CQTE. The proposed definition of CQTE does not assume any parametric form for the optimal treatment rule and plays an important role for assessing the incremental value of a set of new variables in optimal treatment decision making conditional on an existing set of prescriptive variables. We then propose novel testing procedures for no CQTE based on kernel estimation of the conditional contrast functions. We show that our test statistics have asymptotically correct size and nonnegligible power against some nonstandard local alternatives. The empirical performance of the proposed tests are evaluated by simulations and an application to an AIDS data set.

James G. Scott, James O. Berger

Source: Ann. Statist., Volume 38, Number 5, 2587--2619.

Abstract:
This paper studies the multiplicity-correction effect of standard Bayesian variable-selection priors in linear regression. Our first goal is to clarify when, and how, multiplicity correction happens automatically in Bayesian analysis, and to distinguish this correction from the Bayesian Ockham’s-razor effect. Our second goal is to contrast empirical-Bayes and fully Bayesian approaches to variable selection through examples, theoretical results and simulations. Considerable differences between the two approaches are found. In particular, we prove a theorem that characterizes a surprising aymptotic discrepancy between fully Bayes and empirical Bayes. This discrepancy arises from a different source than the failure to account for hyperparameter uncertainty in the empirical-Bayes estimate. Indeed, even at the extreme, when the empirical-Bayes estimate converges asymptotically to the true variable-inclusion probability, the potential for a serious difference remains.

Trang Quynh Nguyen, Elizabeth A. Stuart.

Source: The Annals of Applied Statistics, Volume 14, Number 1, 518--520.

Fan Li, Fan Li.

Source: The Annals of Applied Statistics, Volume 13, Number 4, 2389--2415.

Abstract:
Causal or unconfounded descriptive comparisons between multiple groups are common in observational studies. Motivated from a racial disparity study in health services research, we propose a unified propensity score weighting framework, the balancing weights, for estimating causal effects with multiple treatments. These weights incorporate the generalized propensity scores to balance the weighted covariate distribution of each treatment group, all weighted toward a common prespecified target population. The class of balancing weights include several existing approaches such as the inverse probability weights and trimming weights as special cases. Within this framework, we propose a set of target estimands based on linear contrasts. We further develop the generalized overlap weights, constructed as the product of the inverse probability weights and the harmonic mean of the generalized propensity scores. The generalized overlap weighting scheme corresponds to the target population with the most overlap in covariates across the multiple treatments. These weights are bounded and thus bypass the problem of extreme propensities. We show that the generalized overlap weights minimize the total asymptotic variance of the moment weighting estimators for the pairwise contrasts within the class of balancing weights. We consider two balance check criteria and propose a new sandwich variance estimator for estimating the causal effects with generalized overlap weights. We apply these methods to study the racial disparities in medical expenditure between several racial groups using the 2009 Medical Expenditure Panel Survey (MEPS) data. Simulations were carried out to compare with existing methods.

Bret Zeldow, Vincent Lo Re III, Jason Roy.

Source: The Annals of Applied Statistics, Volume 13, Number 3, 1989--2010.

Abstract:
Bayesian Additive Regression Trees (BART) is a flexible machine learning algorithm capable of capturing nonlinearities between an outcome and covariates and interactions among covariates. We extend BART to a semiparametric regression framework in which the conditional expectation of an outcome is a function of treatment, its effect modifiers, and confounders. The confounders are allowed to have unspecified functional form, while treatment and effect modifiers that are directly related to the research question are given a linear form. The result is a Bayesian semiparametric linear regression model where the posterior distribution of the parameters of the linear part can be interpreted as in parametric Bayesian regression. This is useful in situations where a subset of the variables are of substantive interest and the others are nuisance variables that we would like to control for. An example of this occurs in causal modeling with the structural mean model (SMM). Under certain causal assumptions, our method can be used as a Bayesian SMM. Our methods are demonstrated with simulation studies and an application to dataset involving adults with HIV/Hepatitis C coinfection who newly initiate antiretroviral therapy. The methods are available in an R package called semibart.

Joseph Antonelli, Giovanni Parmigiani, Francesca Dominici.

Source: Bayesian Analysis, Volume 14, Number 3, 825--848.

Abstract:
In observational studies, estimation of a causal effect of a treatment on an outcome relies on proper adjustment for confounding. If the number of the potential confounders ( $p$ ) is larger than the number of observations ( $n$ ), then direct control for all potential confounders is infeasible. Existing approaches for dimension reduction and penalization are generally aimed at predicting the outcome, and are less suited for estimation of causal effects. Under standard penalization approaches (e.g. Lasso), if a variable $X_{j}$ is strongly associated with the treatment $T$ but weakly with the outcome $Y$ , the coefficient $eta_{j}$ will be shrunk towards zero thus leading to confounding bias. Under the assumption of a linear model for the outcome and sparsity, we propose continuous spike and slab priors on the regression coefficients $eta_{j}$ corresponding to the potential confounders $X_{j}$ . Specifically, we introduce a prior distribution that does not heavily shrink to zero the coefficients ( $eta_{j}$ s) of the $X_{j}$ s that are strongly associated with $T$ but weakly associated with $Y$ . We compare our proposed approach to several state of the art methods proposed in the literature. Our proposed approach has the following features: 1) it reduces confounding bias in high dimensional settings; 2) it shrinks towards zero coefficients of instrumental variables; and 3) it achieves good coverages even in small sample sizes. We apply our approach to the National Health and Nutrition Examination Survey (NHANES) data to estimate the causal effects of persistent pesticide exposure on triglyceride levels.

Julyan Arbel, Pierpaolo De Blasi, Igor Prünster.

Source: Bayesian Analysis, Volume 14, Number 3, 753--771.

Abstract:
In this paper we consider approximations to the popular Pitman–Yor process obtained by truncating the stick-breaking representation. The truncation is determined by a random stopping rule that achieves an almost sure control on the approximation error in total variation distance. We derive the asymptotic distribution of the random truncation point as the approximation error $epsilon$ goes to zero in terms of a polynomially tilted positive stable random variable. The practical usefulness and effectiveness of this theoretical result is demonstrated by devising a sampling algorithm to approximate functionals of the $epsilon$ -version of the Pitman–Yor process.

Luis Gutiérrez, Andrés F. Barrientos, Jorge González, Daniel Taylor-Rodríguez.

Source: Bayesian Analysis, Volume 14, Number 2, 649--675.

Abstract:
We propose a Bayesian nonparametric strategy to test for differences between a control group and several treatment regimes. Most of the existing tests for this type of comparison are based on the differences between location parameters. In contrast, our approach identifies differences across the entire distribution, avoids strong modeling assumptions over the distributions for each treatment, and accounts for multiple testing through the prior distribution on the space of hypotheses. The proposal is compared to other commonly used hypothesis testing procedures under simulated scenarios. Two real applications are also analyzed with the proposed methodology.

Chris Englund
Jan 5, 2005; 25:247-251
BRIEF COMMUNICATION

Knowledge about objects encompasses not only their prototypical features but also complex, atypical, semantic knowledge (e.g., "Pizza was invented in Naples"). This fMRI study of male and female human participants combines univariate and multivariate analyses to consider the cortical representation of this more complex semantic knowledge. Using the categories of food, people, and places, this study investigates whether access to spatially related geographic semantic knowledge (1) involves the same domain-selective neural representations involved in access to prototypical taste knowledge about food; and (2) elicits activation of neural representations classically linked to places when this geographic knowledge is accessed about food and people. In three experiments using word stimuli, domain-relevant and atypical conceptual access for the categories food, people, and places were assessed. Results uncover two principles of semantic representation: food-selective representations in the left insula continue to be recruited when prototypical taste knowledge is task-irrelevant and under conditions of high cognitive demand; access to geographic knowledge for food and people categories involves the additional recruitment of classically place-selective parahippocampal gyrus, retrosplenial complex, and transverse occipital sulcus. These findings underscore the importance of object category in the representation of a broad range of knowledge, while showing how the cross recruitment of specialized representations may endow the considerable flexibility of our complex semantic knowledge.

SIGNIFICANCE STATEMENT We know not only stereotypical things about objects (an apple is round, graspable, edible) but can also flexibly combine typical and atypical features to form complex concepts (the metaphorical role an apple plays in Judeo-Christian belief). In this fMRI study, we observe that, when atypical geographic knowledge is accessed about food dishes, domain-selective sensorimotor-related cortical representations continue to be recruited, but that regions classically associated with place perception are additionally engaged. This interplay between categorically driven representations, linked to the object being accessed, and the flexible recruitment of semantic stores linked to the content being accessed, provides a potential mechanism for the broad representational repertoire of our semantic system.

Functional recovery after cortical injury, such as stroke, is associated with neural circuit reorganization, but the underlying mechanisms and efficacy of therapeutic interventions promoting neural plasticity in primates are not well understood. Bone marrow mesenchymal stem cell-derived extracellular vesicles (MSC-EVs), which mediate cell-to-cell inflammatory and trophic signaling, are thought be viable therapeutic targets. We recently showed, in aged female rhesus monkeys, that systemic administration of MSC-EVs enhances recovery of function after injury of the primary motor cortex, likely through enhancing plasticity in perilesional motor and premotor cortices. Here, using in vitro whole-cell patch-clamp recording and intracellular filling in acute slices of ventral premotor cortex (vPMC) from rhesus monkeys (Macaca mulatta) of either sex, we demonstrate that MSC-EVs reduce injury-related physiological and morphologic changes in perilesional layer 3 pyramidal neurons. At 14-16 weeks after injury, vPMC neurons from both vehicle- and EV-treated lesioned monkeys exhibited significant hyperexcitability and predominance of inhibitory synaptic currents, compared with neurons from nonlesioned control brains. However, compared with vehicle-treated monkeys, neurons from EV-treated monkeys showed lower firing rates, greater spike frequency adaptation, and excitatory:inhibitory ratio. Further, EV treatment was associated with greater apical dendritic branching complexity, spine density, and inhibition, indicative of enhanced dendritic plasticity and filtering of signals integrated at the soma. Importantly, the degree of EV-mediated reduction of injury-related pathology in vPMC was significantly correlated with measures of behavioral recovery. These data show that EV treatment dampens injury-related hyperexcitability and restores excitatory:inhibitory balance in vPMC, thereby normalizing activity within cortical networks for motor function.

SIGNIFICANCE STATEMENT Neuronal plasticity can facilitate recovery of function after cortical injury, but the underlying mechanisms and efficacy of therapeutic interventions promoting this plasticity in primates are not well understood. Our recent work has shown that intravenous infusions of mesenchymal-derived extracellular vesicles (EVs) that are involved in cell-to-cell inflammatory and trophic signaling can enhance recovery of motor function after injury in monkey primary motor cortex. This study shows that this EV-mediated enhancement of recovery is associated with amelioration of injury-related hyperexcitability and restoration of excitatory-inhibitory balance in perilesional ventral premotor cortex. These findings demonstrate the efficacy of mesenchymal EVs as a therapeutic to reduce injury-related pathologic changes in the physiology and structure of premotor pyramidal neurons and support recovery of function.

Four years into the 2030 Agenda, there is still a large gap in data to understand where the world stands in achieving its shared goals, the SDGs. To support [...]

Many teens have taken on the role, but not every Robin was a "boy" wonder

The planet's temperatures spike around the latitudes where auroras show up

We’re really, really sorry

Earth’s sister planet spins slowly, but its atmosphere whips around at high speeds

A planned exhibition at the Portland Art Museum highlights the boldness of their work

64-year-old John Neville, in agony and needing his wisdom tooth extracted, has been navigating a complex tangle of COVID-19 restrictions in an unsuccessful attempt at getting emergency dental care.

Press release about the Basel Committee publishing consultation paper on revisions to the credit valuation adjustment risk framework, 28 November 2019.

Press release: Basel Committee invites comments on the design of a prudential treatment for crypto-assets, 12 December 2019.

While the STM is strongly urging passengers to wear a face mask or face covering at all times, it won't be mandatory, said chair Philippe Schnobb.

As a result of the pandemic, USPS, which has run at a loss for years, is even more cash-strapped. It expects to lose $2 billion each month during the pandemic. That prompted Postmaster General Megan Brennan to ask Congress for $50 billion in funds -- $25 billion to offset lost revenue from declining mail volume due to the pandemic, and another $25 billion for modernization.

OM Hungary team members put on a special Christmas programme a local refugee camp.

OM Hungary’s Christmas puppet ministry is currently underway, with performances in the city of Érd and the surrounding area.

An OM short-term team worships God and engages in conversations about God in the public square of a city with an Arab majority in Israel.

God answers the prayers of OM Guatemala and a partnering church with a Christmas celebration for children and families with OM’s Project Rescue.

OM Hong Kong hosts a Christmas party on 23 December 2011 for Pakistani women and children.

BACKGROUND AND OBJECTIVES:

Use of specific services may help to optimize health for children with autism spectrum disorder (ASD); however, little is known about their service use patterns. We aimed to (1) define service use groups and (2) determine associations of sociodemographic, developmental, behavioral, and health characteristics with service use groups among school-aged children with ASD.

BACKGROUND:

Emergency department (ED) care processes and environments impose unique challenges for children with autism spectrum disorder (ASD). The implementation of patient- and family-centered care (PFCC) emerges as a priority for optimizing ED care. In this article, as part of a larger study, we explore PFCC in the context of ASD. Our aims were to examine how elements of PFCC were experienced and applied relative to ED care for children with ASD.

BACKGROUND AND OBJECTIVES:

Families of children with autism spectrum disorder (ASD) often experience challenges navigating multiple systems to access services. Family navigation (FN) is a model to provide information and support to access appropriate services. Few studies have been used to examine FN’s effectiveness for families of children with ASD. This study used mixed methods to (1) characterize FN services received by a sample of families in the Autism Treatment Network; (2) examine change in parent-reported activation, family functioning, and caregiver strain; and (3) explore families’ experiences with FN services.

Family involvement in the Autism Intervention Research Network on Physical Health, the Autism Treatment Network, and the Autism Learning Health Network, jointly the Autism Networks, has evolved and grown into a meaningful and robust collaboration between families, providers, and researchers. Family involvement at the center of the networks includes both local and national network-wide coproduction and contribution. Family involvement includes actively co-authoring research proposals for large grants, equal membership of network committees and workgroups, and formulating quality improvement pathways for local recruitment efforts and other network initiatives. Although families are involved in every aspect of network activity, families have been the driving force of specifically challenging the networks to concentrate research, education, and dissemination efforts around 3 pillar initiatives of addressing comorbidities of anxiety, attention-deficit/hyperactivity disorder, and irritability in autism during the networks’ upcoming funding cycle. The expansion of the networks’ Extension for Community Healthcare Outcomes program is an exciting network initiative that brings best practices in autism care to community providers. As equal hub members of each Extension for Community Healthcare Outcomes team, families ensure that participants are intimately cognizant of family perspectives and goals. Self-advocacy involvement in the networks is emerging, with plans for each site to have self-advocacy representation by the spring of 2020 and ultimately forming their own coproduction committee. The Autism Treatment Network, the Autism Intervention Research Network on Physical Health, and the Autism Learning Health Network continue to be trailblazing organizations in how families are involved in the growth of their networks, production of meaningful research, and dissemination of information to providers and families regarding emerging work in autism spectrum disorders.

The Autism Treatment Network and Autism Intervention Research Network on Physical Health were established in 2008 with goals of improving understanding of the medical aspects of autism spectrum disorders. Over the past decade, the combined network has conducted >2 dozen clinical studies, established clinical pathways for best practice, developed tool kits for professionals and families to support better care, and disseminated these works through numerous presentations at scientific meetings and publications in medical journals. As the joint network enters its second decade continuing this work, it is undergoing a transformation to increase these activities and accelerate their incorporation into clinical care at the primary care and specialty care levels. In this article, we describe the past accomplishments and present activities. We also outline planned undertakings such as the establishment of the Autism Learning Health Network, the increasing role of family members as co-producers of the work of the network, the growth of clinical trials activities with funding from foundations and industry, and expansion of work with primary care practices and autism specialty centers. We also discuss the challenges of supporting network activities and potential solutions to sustain the network.

Acne vulgaris is an extraordinarily common skin condition in adolescents. The mainstays of acne treatment have remained largely unchanged over recent years. In the context of increasing antibiotic resistance worldwide, there is a global movement away from antibiotic monotherapy toward their more restrictive use. Classically reserved for nodulocystic acne, isotretinoin has become the drug of choice by dermatologists for moderate to severe acne. Given the virtually ubiquitous nature of acne in teenagers, there remains an appreciable need for novel therapies. In this article, we will cover the currently used acne treatments, evaluate the issues and data supporting their use, explore the issues of compliance and the mental health implications of acne care, and recommend directions for the field of acne management in adolescents in the years ahead.

The Creative Arts team perform their Christmas show for school children all over Ireland in the course of three weeks.

Historically returns are high.

Anecdotal evidence suggests that institutional investors in South Africa and across the globe are starting to take their ownership rights more seriously.