François Bachoc, José Betancourt, Reinhard Furrer, Thierry Klein.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1962--2008.

Abstract:
The asymptotic analysis of covariance parameter estimation of Gaussian processes has been subject to intensive investigation. However, this asymptotic analysis is very scarce for non-Gaussian processes. In this paper, we study a class of non-Gaussian processes obtained by regular non-linear transformations of Gaussian processes. We provide the increasing-domain asymptotic properties of the (Gaussian) maximum likelihood and cross validation estimators of the covariance parameters of a non-Gaussian process of this class. We show that these estimators are consistent and asymptotically normal, although they are defined as if the process was Gaussian. They do not need to model or estimate the non-linear transformation. Our results can thus be interpreted as a robustness of (Gaussian) maximum likelihood and cross validation towards non-Gaussianity. Our proofs rely on two technical results that are of independent interest for the increasing-domain asymptotic literature of spatial processes. First, we show that, under mild assumptions, coefficients of inverses of large covariance matrices decay at an inverse polynomial rate as a function of the corresponding observation location distances. Second, we provide a general central limit theorem for quadratic forms obtained from transformed Gaussian processes. Finally, our asymptotic results are illustrated by numerical simulations.

Patrick L. Combettes, Christian L. Müller.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 207--238.

Abstract:
We introduce a flexible optimization model for maximum likelihood-type estimation (M-estimation) that encompasses and generalizes a large class of existing statistical models, including Huber’s concomitant M-estimator, Owen’s Huber/Berhu concomitant estimator, the scaled lasso, support vector machine regression, and penalized estimation with structured sparsity. The model, termed perspective M-estimation, leverages the observation that convex M-estimators with concomitant scale as well as various regularizers are instances of perspective functions, a construction that extends a convex function to a jointly convex one in terms of an additional scale variable. These nonsmooth functions are shown to be amenable to proximal analysis, which leads to principled and provably convergent optimization algorithms via proximal splitting. We derive novel proximity operators for several perspective functions of interest via a geometrical approach based on duality. We then devise a new proximal splitting algorithm to solve the proposed M-estimation problem and establish the convergence of both the scale and regression iterates it produces to a solution. Numerical experiments on synthetic and real-world data illustrate the broad applicability of the proposed framework.

Cheryl Flynn, Patrick Perry.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 731--768.

Abstract:
Biclustering, the process of simultaneously clustering the rows and columns of a data matrix, is a popular and effective tool for finding structure in a high-dimensional dataset. Many biclustering procedures appear to work well in practice, but most do not have associated consistency guarantees. To address this shortcoming, we propose a new biclustering procedure based on profile likelihood. The procedure applies to a broad range of data modalities, including binary, count, and continuous observations. We prove that the procedure recovers the true row and column classes when the dimensions of the data matrix tend to infinity, even if the functional form of the data distribution is misspecified. The procedure requires computing a combinatorial search, which can be expensive in practice. Rather than performing this search directly, we propose a new heuristic optimization procedure based on the Kernighan-Lin heuristic, which has nice computational properties and performs well in simulations. We demonstrate our procedure with applications to congressional voting records, and microarray analysis.

Andreas Anastasiou, Robert E. Gaunt.

Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 1, 136--149.

Abstract:
We use the delta method and Stein’s method to derive, under regularity conditions, explicit upper bounds for the distributional distance between the distribution of the maximum likelihood estimator (MLE) of a $d$-dimensional parameter and its asymptotic multivariate normal distribution. Our bounds apply in situations in which the MLE can be written as a function of a sum of i.i.d. $t$-dimensional random vectors. We apply our general bound to establish a bound for the multivariate normal approximation of the MLE of the normal distribution with unknown mean and variance.

Sylvia Frühwirth-Schnatter.

Source: Brazilian Journal of Probability and Statistics, Volume 33, Number 4, 706--733.

Abstract:
Finite mixture models and their extensions to Markov mixture and mixture of experts models are very popular in analysing data of various kind. A challenge for these models is choosing the number of components based on marginal likelihoods. The present paper suggests two innovative, generic bridge sampling estimators of the marginal likelihood that are based on constructing balanced importance densities from the conditional densities arising during Gibbs sampling. The full permutation bridge sampling estimator is derived from considering all possible permutations of the mixture labels for a subset of these densities. For the double random permutation bridge sampling estimator, two levels of random permutations are applied, first to permute the labels of the MCMC draws and second to randomly permute the labels of the conditional densities arising during Gibbs sampling. Various applications show very good performance of these estimators in comparison to importance and to reciprocal importance sampling estimators derived from the same importance densities.

George Karabatsos, Fabrizio Leisen.

Source: Statistics Surveys, Volume 12, 66--104.

Abstract:
We are living in the big data era, as current technologies and networks allow for the easy and routine collection of data sets in different disciplines. Bayesian Statistics offers a flexible modeling approach which is attractive for describing the complexity of these datasets. These models often exhibit a likelihood function which is intractable due to the large sample size, high number of parameters, or functional complexity. Approximate Bayesian Computational (ABC) methods provides likelihood-free methods for performing statistical inferences with Bayesian models defined by intractable likelihood functions. The vastity of the literature on ABC methods created a need to review and relate all ABC approaches so that scientists can more readily understand and apply them for their own work. This article provides a unifying review, general representation, and classification of all ABC methods from the view of approximate likelihood theory. This clarifies how ABC methods can be characterized, related, combined, improved, and applied for future research. Possible future research in ABC is then outlined.

The $p$-tensor Curie-Weiss model is a two-parameter discrete exponential family for modeling dependent binary data, where the sufficient statistic has a linear term and a term with degree $p geq 2$. This is a special case of the tensor Ising model and the natural generalization of the matrix Curie-Weiss model, which provides a convenient mathematical abstraction for capturing, not just pairwise, but higher-order dependencies. In this paper we provide a complete description of the limiting properties of the maximum likelihood (ML) estimates of the natural parameters, given a single sample from the $p$-tensor Curie-Weiss model, for $p geq 3$, complementing the well-known results in the matrix ($p=2$) case (Comets and Gidas (1991)). Our results unearth various new phase transitions and surprising limit theorems, such as the existence of a 'critical' curve in the parameter space, where the limiting distribution of the ML estimates is a mixture with both continuous and discrete components. The number of mixture components is either two or three, depending on, among other things, the sign of one of the parameters and the parity of $p$. Another interesting revelation is the existence of certain 'special' points in the parameter space where the ML estimates exhibit a superefficiency phenomenon, converging to a non-Gaussian limiting distribution at rate $N^{frac{3}{4}}$. We discuss how these results can be used to construct confidence intervals for the model parameters and, as a byproduct of our analysis, obtain limit theorems for the sample mean, which provide key insights into the statistical properties of the model.

Sparse estimation via penalized likelihood (PL) is now a popular approach to learn the associations among a large set of variables. This paper describes an R package called lslx that implements PL methods for semi-confirmatory structural equation modeling (SEM). In this semi-confirmatory approach, each model parameter can be specified as free/fixed for theory testing, or penalized for exploration. By incorporating either a L1 or minimax concave penalty, the sparsity pattern of the parameter matrix can be efficiently explored. Package lslx minimizes the PL criterion through a quasi-Newton method. The algorithm conducts line search and checks the first-order condition in each iteration to ensure the optimality of the obtained solution. A numerical comparison between competing packages shows that lslx can reliably find PL estimates with the least time. The current package also supports other advanced functionalities, including a two-stage method with auxiliary variables for missing data handling and a reparameterized multi-group SEM to explore population heterogeneity.

Niansheng Tang, Xiaodong Yan, Xingqiu Zhao.

Source: The Annals of Statistics, Volume 48, Number 1, 607--627.

Abstract:
This article considers simultaneous variable selection and parameter estimation as well as hypothesis testing in censored survival models where a parametric likelihood is not available. For the problem, we utilize certain growing dimensional general estimating equations and propose a penalized generalized empirical likelihood, where the general estimating equations are constructed based on the semiparametric efficiency bound of estimation with given moment conditions. The proposed penalized generalized empirical likelihood estimators enjoy the oracle properties, and the estimator of any fixed dimensional vector of nonzero parameters achieves the semiparametric efficiency bound asymptotically. Furthermore, we show that the penalized generalized empirical likelihood ratio test statistic has an asymptotic central chi-square distribution. The conditions of local and restricted global optimality of weighted penalized generalized empirical likelihood estimators are also discussed. We present a two-layer iterative algorithm for efficient implementation, and investigate its convergence property. The performance of the proposed methods is demonstrated by extensive simulation studies, and a real data example is provided for illustration.

Emmanuel J. Candès, Pragya Sur.

Source: The Annals of Statistics, Volume 48, Number 1, 27--42.

Abstract:
This paper rigorously establishes that the existence of the maximum likelihood estimate (MLE) in high-dimensional logistic regression models with Gaussian covariates undergoes a sharp “phase transition.” We introduce an explicit boundary curve $h_{mathrm{MLE}}$, parameterized by two scalars measuring the overall magnitude of the unknown sequence of regression coefficients, with the following property: in the limit of large sample sizes $n$ and number of features $p$ proportioned in such a way that $p/n ightarrow kappa $, we show that if the problem is sufficiently high dimensional in the sense that $kappa >h_{mathrm{MLE}}$, then the MLE does not exist with probability one. Conversely, if $kappa <h_{mathrm{MLE}}$, the MLE asymptotically exists with probability one.

Francesco Bravo, Juan Carlos Escanciano, Ingrid Van Keilegom.

Source: The Annals of Statistics, Volume 48, Number 1, 1--26.

Abstract:
In both parametric and certain nonparametric statistical models, the empirical likelihood ratio satisfies a nonparametric version of Wilks’ theorem. For many semiparametric models, however, the commonly used two-step (plug-in) empirical likelihood ratio is not asymptotically distribution-free, that is, its asymptotic distribution contains unknown quantities, and hence Wilks’ theorem breaks down. This article suggests a general approach to restore Wilks’ phenomenon in two-step semiparametric empirical likelihood inferences. The main insight consists in using as the moment function in the estimating equation the influence function of the plug-in sample moment. The proposed method is general; it leads to a chi-squared limiting distribution with known degrees of freedom; it is efficient; it does not require undersmoothing; and it is less sensitive to the first-step than alternative methods, which is particularly appealing for high-dimensional settings. Several examples and simulation studies illustrate the general applicability of the procedure and its excellent finite sample performance relative to competing methods.

Antony Overstall, James McGree.

Source: Bayesian Analysis, Volume 15, Number 1, 103--131.

Abstract:
A Bayesian design is given by maximising an expected utility over a design space. The utility is chosen to represent the aim of the experiment and its expectation is taken with respect to all unknowns: responses, parameters and/or models. Although straightforward in principle, there are several challenges to finding Bayesian designs in practice. Firstly, the utility and expected utility are rarely available in closed form and require approximation. Secondly, the design space can be of high-dimensionality. In the case of intractable likelihood models, these problems are compounded by the fact that the likelihood function, whose evaluation is required to approximate the expected utility, is not available in closed form. A strategy is proposed to find Bayesian designs for intractable likelihood models. It relies on the development of an automatic, auxiliary modelling approach, using multivariate Gaussian process emulators, to approximate the likelihood function. This is then combined with a copula-based approach to approximate the marginal likelihood (a quantity commonly required to evaluate many utility functions). These approximations are demonstrated on examples of stochastic process models involving experimental aims of both parameter estimation and model comparison.

Lutz F. Gruber, Erica F. Stuber, Lyndsie S. Wszola, Joseph J. Fontaine.

Source: Bayesian Analysis, Volume 14, Number 4, 1173--1199.

Abstract:
We present an integrated open population model where the population dynamics are defined by a differential equation, and the related statistical model utilizes a Poisson binomial convolution likelihood. Key advantages of the proposed approach over existing open population models include the flexibility to predict related, but unobserved quantities such as total immigration or emigration over a specified time period, and more computationally efficient posterior simulation by elimination of the need to explicitly simulate latent immigration and emigration. The viability of the proposed method is shown in an in-depth analysis of outdoor recreation participation on public lands, where the surveyed populations changed rapidly and demographic population closure cannot be assumed even within a single day.

Claudia Kirch, Matthew C. Edwards, Alexander Meier, Renate Meyer.

Source: Bayesian Analysis, Volume 14, Number 4, 1037--1073.

Abstract:
Nonparametric Bayesian inference has seen a rapid growth over the last decade but only few nonparametric Bayesian approaches to time series analysis have been developed. Most existing approaches use Whittle’s likelihood for Bayesian modelling of the spectral density as the main nonparametric characteristic of stationary time series. It is known that the loss of efficiency using Whittle’s likelihood can be substantial. On the other hand, parametric methods are more powerful than nonparametric methods if the observed time series is close to the considered model class but fail if the model is misspecified. Therefore, we suggest a nonparametric correction of a parametric likelihood that takes advantage of the efficiency of parametric models while mitigating sensitivities through a nonparametric amendment. We use a nonparametric Bernstein polynomial prior on the spectral density with weights induced by a Dirichlet process and prove posterior consistency for Gaussian stationary time series. Bayesian posterior computations are implemented via an MH-within-Gibbs sampler and the performance of the nonparametrically corrected likelihood for Gaussian time series is illustrated in a simulation study and in three astronomy applications, including estimating the spectral density of gravitational wave data from the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO).

Peste des petits ruminants (PPR) or sheep and goat plague is a highly contagious animal disease affecting small ruminants. An estimated 300 million families who rely on small ruminants, such as sheep and goats, as a source of food and income are at risk of losing their livelihoods and may be forced to migrate, particularly in areas where food insecurity, other resource shortages [...]

Many of us look back on our childhoods with warm feelings. But for more than 150 million girls and boys between the ages of 5 and 17 around the world, childhood means something else: poverty, a lack of education and working long hours in dangerous conditions.  

The cats also cross the road an average of 4.5 times in six days, putting themselves in danger

The Flint Water Crisis captured national attention about the dangers of lead contamination in public water supplies. Now, nearly six years after the problem was first detected, health officials are reporting on the well-being of children in Flint.

Vancouver police are investigating an incident where a man attempted to lure a child to his car in the city’s West Point Grey neighbourhood on Wednesday.

As a child, Fay Richardson wanted to dance, with the grace and movement of ballet captivating her. Now, at 79-years-old, she's doing just that.

Denver Newsroom, May 7, 2020 / 06:01 pm (CNA).- A young Catholic artist has drawn an image of the Blessed Virgin Mary on her parents' driveway bringing religious art to her local community during the quarantine.

The Diocese of Fargo posted on Facebook May 4 an image of Our Lady of Lourdes drawn by Maria Loh, a 17-year old who grew up in Fargo. She said it was an enjoyable experience to share her faith and art with her neighborhood.

“Being able to interact with people when they walked by was very moving in a way because a lot of people have never really seen sidewalk art done like that locally. So being able to share in that kind of experience, it was very, very good,” she told CNA.

Loh has recently been inspired by chalk art and pastels, which, she said, have vibrant and beautiful colors. She has drawn on the sidewalks a few times, including two images of Mary - Madonna of the Lillies and the Pieta by William Adolphe-Bouguereau.

Her most recent chalk drawing was Our Lady of Lourdes by Hector Garrido - an image she had seen as a magnet on her grandparents' refrigerator growing up. The picture has always been an inspiration, she said, noting that she decided to replicate it after Our Lady of Lourdes Shrine in France had temporarily closed due to the coronavirus pandemic.

“I heard that the shrine had been temporarily closed off to the public, and I remember … thinking that's really sad because especially in this time, we’re really looking for healing in more ways than one, like physically and mentally and spiritually,” she said.

“It really felt like people wouldn't be able to go to experience that. So I felt like drawing this image of Our Lady of Lourdes would be a good way to remind people that Our Lady is still with us even if we can’t go to her shrine.”

Loh, the oldest of five, has been involved with art projects and drawing for her entire life. She said, growing up in a Catholic family, she has been inspired by her faith and the religious art in churches.

“I see our faith as so precious... Especially in the form of the Eucharist - the actual body and blood of Christ, I've seen that we are very blessed to have that in our faith. It's something that has impacted a lot of my life growing up,” she said.

While she was working on the piece, Loh said, a majority of passersby did not know who the lady in the image was. She expressed hope that the picture would help remind people of Mary and the beauty of the Church, which, she said, is a powerful attraction to the faith.

“One thing that I hope this kind of art and image will evoke is a desire to come to know who Mary is and how rich our faith is. … All the beautiful art that can be seen in Catholic churches, especially like in Rome, there's almost a transcendental beauty to them that draws people into the faith to come to know things that they've never dreamed of before,” she said.

As Loh finishes her junior year of high school, she expressed the possibility of art school after graduation, but, while she is still uncertain of the future, said art will not be dropped anytime soon.

“I can definitely see [art school] being a possibility. I’ll have to spend some time, especially with God trying to figure out what he wants me to do. But, I don't think art is going out of my life anytime soon,” she said.

CNA Staff, May 7, 2020 / 07:00 am (CNA).- The sainthood causes of St. John Paul II’s parents were formally opened in Poland Thursday.

A ceremony launching the causes of Karol and Emilia Wojtyła took place at the Basilica of the Presentation of the Blessed Virgin Mary in Wadowice, John Paul II’s birthplace, May 7. 

At the ceremony, the Archdiocese of Kraków officially formed the tribunals that will seek evidence that the Polish pope’s parents lived lives of heroic virtue, enjoy a reputation for holiness and are regarded as intercessors. 

After the tribunals’ first session, Kraków Archbishop Marek Jędraszewski presided at a Mass, which was broadcast via livestream amid Poland’s coronavirus lockdown. 

Cardinal Stanisław Dziwisz, who served as Pope John Paul II’s personal secretary, attended the ceremony.

He said: “I want to testify here, at this point, in the presence of the archbishop and the assembled priests, that as a long-standing secretary of Cardinal Karol Wojtyła and Pope John Paul II, I heard from him many times that he had holy parents.”

Fr. Paweł Rytel-Andrianik, spokesman for the Polish bishops’ conference, told CNA: “The processes of beatification of Karol and Emilia Wojtyła ... testify above all to the appreciation of the family and its great role in shaping the holy and great man -- the Polish Pope.” 

“The Wojtyłas were able to create such an atmosphere at home and form children in such a way that they became outstanding people.” 

“Therefore, there is great joy of starting the beatification processes and great gratitude to God for the life of Emilia and Karol Wojtyła and for the fact that we will be able to get to know them more and more. They will become a model and example for many families who want to be holy.”

Postulator Fr. Sławomir Oder, who also oversaw the cause of John Paul II, told Vatican News that the ceremony was an occasion for rejoicing in Poland. 

He said: “In fact, looking at this event, I am reminded of the words that John Paul II pronounced during the Mass of canonization of St. Kinga, known as Cunegonda, celebrated in Poland in Stary Sącz, when he said that saints are born of saints, are nurtured by the saints, draw life from the saints and their call to holiness.” 

“And in that context he spoke precisely of the family as the privileged place where holiness finds its roots, the first sources where it can mature throughout life.”

The Basilica of the Presentation, where the Wojtyłas' cause was opened, is where St. John Paul II was baptised on June 20, 1920. The church is located across the street from the Wojtyła family home, which is now a museum, in Wadowice.

Karol Wojtyła, an army officer, and Emilia, a school teacher, were married in Kraków in 1906. They had three children. The first, Edmund, was born that year. He became a doctor but caught scarlet fever from a patient and died in 1932. Their second child, Olga, died shortly after birth in 1916. Their youngest, Karol junior, was born in 1920, after Emilia refused a doctor’s advice to have an abortion because of her frail health. 

Emilia worked as a part-time seamstress after her third child’s birth. She died on April 13, 1929, shortly before Karol junior’s ninth birthday, of myocarditis and renal failure, according to her death certificate.

Karol senior, who was born on July 18, 1879, was a non-commissioned officer of the Austro-Hungarian army and a captain of the Polish army. He died on Feb. 18, 1941, in Kraków amid the Nazi occupation of Poland.

The future pope, who was 20 at the time and working at a stone quarry, returned from work to find his father’s body. He spent the night praying beside the body and afterwards began to pursue his vocation to the priesthood. 

Denver Newsroom, May 7, 2020 / 06:01 pm (CNA).- A young Catholic artist has drawn an image of the Blessed Virgin Mary on her parents' driveway bringing religious art to her local community during the quarantine.

The Diocese of Fargo posted on Facebook May 4 an image of Our Lady of Lourdes drawn by Maria Loh, a 17-year old who grew up in Fargo. She said it was an enjoyable experience to share her faith and art with her neighborhood.

“Being able to interact with people when they walked by was very moving in a way because a lot of people have never really seen sidewalk art done like that locally. So being able to share in that kind of experience, it was very, very good,” she told CNA.

Loh has recently been inspired by chalk art and pastels, which, she said, have vibrant and beautiful colors. She has drawn on the sidewalks a few times, including two images of Mary - Madonna of the Lillies and the Pieta by William Adolphe-Bouguereau.

Her most recent chalk drawing was Our Lady of Lourdes by Hector Garrido - an image she had seen as a magnet on her grandparents' refrigerator growing up. The picture has always been an inspiration, she said, noting that she decided to replicate it after Our Lady of Lourdes Shrine in France had temporarily closed due to the coronavirus pandemic.

“I heard that the shrine had been temporarily closed off to the public, and I remember … thinking that's really sad because especially in this time, we’re really looking for healing in more ways than one, like physically and mentally and spiritually,” she said.

“It really felt like people wouldn't be able to go to experience that. So I felt like drawing this image of Our Lady of Lourdes would be a good way to remind people that Our Lady is still with us even if we can’t go to her shrine.”

Loh, the oldest of five, has been involved with art projects and drawing for her entire life. She said, growing up in a Catholic family, she has been inspired by her faith and the religious art in churches.

“I see our faith as so precious... Especially in the form of the Eucharist - the actual body and blood of Christ, I've seen that we are very blessed to have that in our faith. It's something that has impacted a lot of my life growing up,” she said.

While she was working on the piece, Loh said, a majority of passersby did not know who the lady in the image was. She expressed hope that the picture would help remind people of Mary and the beauty of the Church, which, she said, is a powerful attraction to the faith.

“One thing that I hope this kind of art and image will evoke is a desire to come to know who Mary is and how rich our faith is. … All the beautiful art that can be seen in Catholic churches, especially like in Rome, there's almost a transcendental beauty to them that draws people into the faith to come to know things that they've never dreamed of before,” she said.

As Loh finishes her junior year of high school, she expressed the possibility of art school after graduation, but, while she is still uncertain of the future, said art will not be dropped anytime soon.

“I can definitely see [art school] being a possibility. I’ll have to spend some time, especially with God trying to figure out what he wants me to do. But, I don't think art is going out of my life anytime soon,” she said.

Having a bachelor's degree, a top-notch grade point average, and a relatively high level of work experience actually reduce the chance that a job applicant will be called in for an interview with a child-care provider, concludes new research by Kent State and Arizona State universities.

New data show that a growing percentage of children, especially those from well-off households, attend center-based care in the year before they attend kindergarten.

There's a new focus on getting more training to early-childhood educators, but there's a dearth of information about what constitutes a high-quality, teacher-preparation program.

The Center for American Progress has released a set of recommendations for governors in 2019 that includes things such as full-day universal preschool and the study of pre-term births, which can cause learning difficulties.

Half of Americans in 22 states live in "child-care deserts"—places where there are more than three children for every child-care slot—according to a new geographic analysis by the Center on American Progress, a liberal think tank.

Without rigorous research that accurately reflects the current population, early education won't deliver for all students, write two education researchers.

Democrat Gavin Newsom, who takes office Jan. 7, plans to expand full-day kindergarten and child-care offerings in the state, according to media reports.

Federal funding for state-administered child-care-assistance programs has declined since 2001, leaving many low-income families struggling to find child care, finds a study by the National Women's Law Center.

Families may be less likely to take advantage of early-childhood education programs if they work nonstandard hours, finds a new report from the National Research Center on Hispanic Children and Families.

Education needs to stop going around in circles, writes Stanford’s Thomas S. Dee.

Waterford UPSTART, an online program that offers literacy and math enrichment lessons aimed at preschoolers, received support from a philanthropy dedicated to funding "bold ideas for social change."

The World Health Organization issued guidelines for children under 5, including its first recommendations on how much time children should be spending in front of a digital screen.

A new report by the Government Accountability Office provides the first comprehensive nationwide look at state early education programs and how they are funded.

Pediatric weight gain is a critical aspect of the obesity epidemic. Chronic stress produces physiologic perturbations capable of altering brain mechanisms related to eating as well as those implicated in self-regulatory behaviors.

We show that early childhood risk exposures are associated with weight gain in adolescence, independent of childhood BMI. We also find that deficiencies in self-regulatory processes help explain the link between chronic stress and adiposity. (Read the full article)

Overweight has been associated with an increased risk of asthma in children, although the published literature is contradictory. How change in overweight status during childhood affects asthma risk has not been well studied.

Among children whose weight has normalized, high BMI during the first 4 years of life does not increase the risk of asthma at school age. Current high BMI is associated with increased risk of asthma and sensitization to inhalant allergens. (Read the full article)

Traumatic brain injury in school-aged children is associated with intellectual, behavioral, and social deficits. Research into outcomes of children injured before 3 years of age is limited despite data suggesting a high incidence of injury in this age group.

Results show that a moderate to severe traumatic brain injury before 3 years of age is associated with lowered cognitive function. Furthermore, this study highlights the link between social disadvantage and poor outcomes after traumatic brain injury in early childhood. (Read the full article)

Epilepsy/seizure disorder is known to be associated with a range of mental health and neurodevelopmental comorbidities, based on clinical studies, and on population studies largely conducted outside the United States.

In a nationally representative sample of US children, estimated prevalence of reported lifetime epilepsy/seizure disorder was 1%, and of current epilepsy/seizure disorder was 6.3/1000. Developmental, mental health, and physical comorbidities are common, warranting enhanced surveillance, and an integrated service approach. (Read the full article)

There are a number of effective interventions designed to prevent childhood/adolescent depression. Such interventions tend to comprise screening and the subsequent provision of psychological therapy. However, the cost-effectiveness of routinely providing such interventions at a population level is not known.

By using economic modeling techniques, this study shows that the population cost-effectiveness of such preventive interventions for childhood/adolescent depression is very favorable, although implementation issues, particularly around the acceptability to providers, need to be addressed before widespread adoption. (Read the full article)

The evidence base for obesity prevention is extremely limited. Although minority youth are at higher risk of obesity, and early childhood is a critical period for prevention, only 1 program has demonstrated sustained effects on obesity in young minority children.

Among youth at high risk for obesity based on income, minority status, and child behavior problems, early intervention that promotes effective parenting led to meaningful differences in obesity in preadolescence. Early family intervention is an innovative and promising approach. (Read the full article)

Atherosclerotic cardiovascular diseases have roots in childhood. Modification of dietary fat intake influences serum lipid and lipoprotein concentrations. Reduction of saturated fat intake is recommended to promote cardiovascular health.

Dietary counseling had a beneficial effect on saturated fat intake from ages 7 months to 19 years. The counseling reduced serum low-density lipoprotein cholesterol concentrations in both genders. It also decreased computationally estimated concentrations of intermediate-density lipoprotein cholesterol, very low-density lipoprotein–triglycerides and apolipoprotein B in boys. (Read the full article)

Childhood gender nonconformity has been associated with poorer relationships with parents, but it is unknown if childhood gender nonconformity is associated with childhood abuse or with posttraumatic stress disorder.

We identify gender nonconformity before age 11 years as a risk indicator for physical, sexual, and psychological abuse in childhood and lifetime probable posttraumatic stress disorder in youth. (Read the full article)

Previous research on the cost of childhood autism has been restricted primarily to studying direct costs (money outlays) incurred by publicly and privately funded service systems.

This study estimates the economic impact on the family and examines indirect costs to families in the form of parental labor market productivity losses. (Read the full article)

Prenatal methamphetamine exposure has been related to deficits in fetal growth, changes in infant neurobehavior, and fine motor deficits, but little is known about its developmental effects on behavior problems in early childhood.

This is the first prospective study to identify behavior problems associated with prenatal methamphetamine exposure. Mood difficulties and acting-out behavior are increased in exposed children by age 3 years. Early identification and intervention may prevent escalation into delinquency and psychopathology. (Read the full article)

Healthcare Effectiveness Data and Information Set (HEDIS) measures are widely used to assess the reliability of pediatric immunization delivery. The extent to which these measures provide accurate ("is this child up-to-date on immunizations?") and useful ("is this child due for catch-up immunizations?") information is unclear.

Overall, HEDIS childhood immunization measures are accurate and useful. Users of HEDIS data should be aware, however, that certain immunizations (eg, hepatitis B, pneumococcal conjugate) and children (eg, those with a single overdue immunization) are more prone to HEDIS misclassification. (Read the full article)