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With clustered data, such as where students are nested within schools or employees are nested within organizations, it is often of interest to estimate and compare associations among variables separately for each level. While researchers routinely estimate between-cluster effects using the sample cluster means of a predictor, previous research has shown that such practice leads to biased estimates of coefficients at the between level, and recent research has recommended the use of latent cluster means with the multilevel structural equation modeling framework. However, the latent cluster mean approach may not always be the best choice as it (a) relies on the assumption that the population cluster sizes are close to infinite, (b) requires a relatively large number of clusters, and (c) is currently only implemented in specialized software such as Mplus. In this paper, we show how using empirical Bayes estimates of the cluster means can also lead to consistent estimates of between-level coefficients, and illustrate how the empirical Bayes estimate can incorporate finite population corrections when information on population cluster sizes is available. Through a series of Monte Carlo simulation studies, we show that the empirical Bayes cluster-mean approach performs similarly to the latent cluster mean approach for estimating the between-cluster coefficients in most conditions when the infinite-population assumption holds, and applying the finite population correction provides reasonable point and interval estimates when the population is finite. The performance of EBM can be further improved with restricted maximum likelihood estimation and likelihood-based confidence intervals. We also provide an R function that implements the empirical Bayes cluster-mean approach, and illustrate it using data from the classic High School and Beyond Study. [ABSTRACT FROM AUTHOR]

Covariance estimation for matrix-valued data has received an increasing interest in applications. Unlike previous works that rely heavily on matrix normal distribution assumption and the requirement of fixed matrix size, we propose a class of distribution-free regularized covariance estimation methods for high-dimensional matrix data under a separability condition and a bandable covariance structure. Under these conditions, the original covariance matrix is decomposed into a Kronecker product of two bandable small covariance matrices representing the variability over row and column directions. We formulate a unified framework for estimating bandable covariance, and introduce an efficient algorithm based on rank one unconstrained Kronecker product approximation. The convergence rates of the proposed estimators are established, and the derived minimax lower bound shows our proposed estimator is rate-optimal under certain divergence regimes of matrix size. We further introduce a class of robust covariance estimators and provide theoretical guarantees to deal with heavy-tailed data. We demonstrate the superior finite-sample performance of our methods using simulations and real applications from a gridded temperature anomalies dataset and an S&P 500 stock data analysis. for this article are available online. [ABSTRACT FROM AUTHOR]

This article examines the emergence and development of playgrounds in the most significant treaty ports of China — Guangzhou, Shanghai, and Tianjin — during the first half of the 20th century. It contributes to understanding the unique evolution of playgrounds and children's play in modern China by exploring the interaction between imported ideas from the endogenous development of playgrounds in Europe and America and new ideas on children's development with local circumstances and social ideas. It reveals that initially, children's play was mainly adult-oriented, but after certain ideas on safety, education, and physical development were introduced, playgrounds were constructed. Later, physical constructions and management methods were added until they developed into particular landscapes that were constructed to meet the perceived physical, social, and mental needs of children. During this process, urban citizens changed their ideology on play, viewing playgrounds as a tool for training children to conform to society. [ABSTRACT FROM AUTHOR]

We present three studies to demonstrate the important role of institutional trust in promoting prosocial behavior in China. In study 1, we used a Chinese national survey and found that institutional trust significantly predicted people's donation and volunteer activities. In study 2, we experimentally examined the effects of institutional trust in public goods games. Participants allocated more money to public accounts when a positive impression of institutions was implicitly activated than when a negative impression or no concepts were activated. In study 3, we tested the effects of institutional trust in a field experiment with a "pay what you want" strategy. In a charity bazaar, participants who received leaflets that implicitly activated institutional concepts paid more money. [ABSTRACT FROM AUTHOR]

There has been tremendous growth in research on measurement invariance over the past two decades. However, given that psychological tests are commonly used for making classification decisions such as personnel selections or diagnoses, surprisingly, there has been little research on how noninvariance impacts classification accuracy. Millsap and Kwok previously proposed a selection accuracy framework for that purpose, which has been recently extended to categorical data. Their framework, however, only deals with classification using a unidimensional test. In contrast, classification in practice usually involves multidimensional tests (e.g., personality) or multiple tests, with different weights assigned to each dimension. In the current paper, we extend Millsap and Kwok's framework for examining the impact of noninvariance to a multidimensional test on classification. We also provide an R script for the proposed method and illustrate it with a personnel selection example using data from a published report featuring a five-factor personality inventory. [ABSTRACT FROM AUTHOR]

A transnational flow of capital exchange during the 19th and early 20th centuries brought planning ideas and modernity into China. Since European countries and America used violence to place China into a colonial world and its forms of power-knowledge, the existing works too often focus on the impact of the 'west', treating the Chinese as passive recipients who responded to 'western' transnational planning ideas, while neglecting the transnational flow of Intra-Asia. By exploring the formation of urbanism in Hebei New Area in Tianjin, this article reveals that the Chinese did not allow themselves to be dictated to by the planning ideas emanating from the west. Instead, they both sought the most suitable ideas based on their local situations and actively imported planning ideas from the east – Japan. The authorities in Tianjin sent officials to Japan to draw upon Japanese industrial and commercial planning models to set up their own organizational framework, urban built environments, and operational management. Consequently, they incorporated planning ideas from the 'east' to re-organize the daily life of the masses and modernize their city. These ideas were juxtaposed with ideas from the 'west' to shape the urbanism of Tianjin. [ABSTRACT FROM AUTHOR]

Computer simulations often involve both qualitative and numerical inputs. Existing Gaussian process (GP) methods for handling this mainly assume a different response surface for each combination of levels of the qualitative factors and relate them via a multiresponse cross-covariance matrix. We introduce a substantially different approach that maps each qualitative factor to underlying numerical latent variables (LVs), with the mapped values estimated similarly to the other correlation parameters, and then uses any standard GP covariance function for numerical variables. This provides a parsimonious GP parameterization that treats qualitative factors the same as numerical variables and views them as affecting the response via similar physical mechanisms. This has strong physical justification, as the effects of a qualitative factor in any physics-based simulation model must always be due to some underlying numerical variables. Even when the underlying variables are many, sufficient dimension reduction arguments imply that their effects can be represented by a low-dimensional LV. This conjecture is supported by the superior predictive performance observed across a variety of examples. Moreover, the mapped LVs provide substantial insight into the nature and effects of the qualitative factors. for the article are available online. [ABSTRACT FROM AUTHOR]

Precision medicine is currently a topic of great interest in clinical and intervention science.  A key component of precision medicine is that it is evidence-based, that is, data-driven, and consequently there has been tremendous interest in estimation of precision medicine strategies using observational or randomized study data. One way to formalize precision medicine is through a treatment regime, which is a sequence of decision rules, one per stage of clinical intervention, that map up-to-date patient information to a recommended treatment. An optimal treatment regime is defined as maximizing the mean of some cumulative clinical outcome if applied to a population of interest. It is well-known that even under simple generative models an optimal treatment regime can be a highly nonlinear function of patient information. Consequently, a focal point of recent methodological research has been the development of flexible models for estimating optimal treatment regimes. However, in many settings, estimation of an optimal treatment regime is an exploratory analysis intended to generate new hypotheses for subsequent research and not to directly dictate treatment to new patients. In such settings, an estimated treatment regime that is interpretable in a domain context may be of greater value than an unintelligible treatment regime built using "black-box" estimation methods. We propose an estimator of an optimal treatment regime composed of a sequence of decision rules, each expressible as a list of "if-then" statements that can be presented as either a paragraph or as a simple flowchart that is immediately interpretable to domain experts. The discreteness of these lists precludes smooth, that is, gradient-based, methods of estimation and leads to nonstandard asymptotics. Nevertheless, we provide a computationally efficient estimation algorithm, prove consistency of the proposed estimator, and derive rates of convergence. We illustrate the proposed methods using a series of simulation examples and application to data from a sequential clinical trial on bipolar disorder. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

The authors express their views on an article on marginal screening in high-dimensional linear regression, that is published in this issue. Topics discussed include statistical screening methods developed by modifying the adaptive resampling test (ART); parametric bootstrap version of ART; and Monte Carlo replications.

Megakaryocytes (MKs) are the unique non-pathological cells that undergo polyploidization in mammals. The polyploid formation is critical for understanding the MK biology, and transcriptional regulation is involved in the differentiation and maturation of MKs. However, little is known about the functions of transcriptional elongation factors in the MK polyploidization. In this study, we investigated the role of transcription elongation factor EloA in the polyploidy formation during the MK differentiation. We found that EloA was highly expressed in the erythroleukemia cell lines HEL and K562. Knockdown of EloA in HEL cell line was shown to impair the phorbol myristate acetate (PMA) induced polyploidization process, which was used extensively to model megakaryocytic differentiation. Selective over-expression of EloA mutants with Pol II elongation activity partially restored the polyploidization. RNA-sequencing revealed that knockdown of EloA decelerated the transcription of genes enriched in the ERK1/2 cascade pathway. The phosphorylation activity of ERK1/2 decreased upon the EloA inhibition, and the polyploidization process of HEL was hindered when ERK1/2 phosphorylation was inhibited by PD0325901 or SCH772984. This study evidenced a positive role of EloA in HEL polyploidization upon PMA stimulation through enhanced ERK1/2 activity. [ABSTRACT FROM AUTHOR]

Inherited thrombocytopenia 2 (THC2) is difficult to diagnose due to the lack of specific clinical characteristics and diagnostic methods. To identify potential plasma protein biomarkers for THC2, we collected the plasma samples from a THC2 family (9 THC2 and 15 non-THC2 members), enriched the medium and low abundant proteins using Proteominer and analyzed the protein profiles using the liquid chromatography-mass spectrometry in data independent acquisition mode. Initially, we detected 784 proteins in the plasma samples of this family and identified 27 up-regulated and 36 down-regulated in the THC2 group compared to the non-THC2 group (|log2 ratio| >1 and p-value <0.05). To improve the predictive power, top eight dysregulated proteins (B7Z2B4, LTF, HP, ERN1, IGHV1-8, A0A0X9V9C4, VH6DJ, and D3JV41) were selected by an area under the curve-based random forest process to construct a clinical model. Multivariate analysis with random forest and support vector machine showed that the prediction model provided high discrimination ability for THC2 diagnosis (AUC: 1.000 and 0.967, respectively). The potential plasma protein biomarkers will be tested in more THC2 patients and other thrombocytopenia patients to further validate their specificity and sensitivity. [ABSTRACT FROM AUTHOR]

Selecting the set of candidate viewpoints (CVs) is one of the most important procedures in multiple viewshed analysis. However, the quantity of CVs remains excessive even when only terrain feature points are selected. Here we propose the Region Partitioning for Filtering (RPF) algorithm, which uses a region partitioning method to filter CVs of a multiple viewshed. The region partitioning method is used to decompose an entire area into several regions. The quality of CVs can be evaluated by summarizing the viewshed area of each CV in each region. First, the RPF algorithm apportions each CV to a region wherein the CV has a larger viewshed than that in other regions. Then, CVs with relatively small viewshed areas are removed from their original regions or reassigned to another region in each iterative step. In this way, a set of high-quality CVs can be preserved, and the size of the preserved CVs can be controlled by the RPF algorithm. To evaluate the computational efficiency of the RPF algorithm, its performance was compared with simple random (SR), simulated annealing (SA), and ant colony optimization (ACO) algorithms. Experimental results indicate that the RPF algorithm provides more than a 20% improvement over the SR algorithm, and that, on average, the computation time of the RPF algorithm is 63% that of the ACO algorithm. [ABSTRACT FROM AUTHOR]

The strain- and polarization-electric field behavior was characterized at room temperature for Pb0.98Ba0.01(Zr1−xTix)0.98Nb0.02O3, 0.40 ⩽ x ⩽ 0.60. The investigated compositions were located in the vicinity of the morphotropic phase boundary, giving insight into the influence of crystal structure on the hysteretic ferroelectric behavior. The remanent strain of particular compositions is shown to be larger than theoretically allowed by ferroelectric switching alone, indicating the presence of additional remanent strain mechanisms. A phenomenological free energy analysis was used to simulate the effect of an applied electric field on the initial equilibrium phase. It is shown that electric-field-induced phase transitions in polycrystalline ferroelectrics can account for the experimental observations. The experimental and simulation results are contrasted to neutron diffraction measurements performed on representative compositions in the virgin and remanent states. [ABSTRACT FROM AUTHOR]