Testing stochastic orders in tails of contingency tables

Testing for the difference in the strength of bivariate association in two independent contingency tables is an important issue that finds applications in various disciplines. Currently, many of the commonly used tests are based on single-index measures of association. More specifically, one obtains single-index measurements of association from two tables and compares them based on asymptotic theory. Although they are usually easy to understand and use, often much of the information contained in the data is lost with single-index measures. Accordingly, they fail to fully capture the association in the data. To remedy this shortcoming, we introduce a new summary statistic measuring various types of association in a contingency table. Based on this new summary statistic, we propose a likelihood ratio test comparing the strength of association in two independent contingency tables. The proposed test examines the stochastic order between summary statistics. We derive its asymptotic null distribution and demonstrate that the least favorable distributions are chi-bar distributions. We numerically compare the power of the proposed test to that of the tests based on single-index measures. Finally, we provide two examples illustrating the new summary statistics and the related tests.     

Spatial Bayesian modeling of GLCM with application to malignant lesion characterization

The emerging field of cancer radiomics endeavors to characterize intrinsic patterns of tumor phenotypes and surrogate markers of response by transforming medical images into objects that yield quantifiable summary statistics to which regression and machine learning algorithms may be applied for statistical interrogation. Recent literature has identified clinicopathological association based on textural features deriving from gray-level co-occurrence matrices (GLCM) which facilitate evaluations of gray-level spatial dependence within a delineated region of interest. GLCM-derived features, however, tend to contribute highly redundant information. Moreover, when reporting selected feature sets, investigators often fail to adjust for multiplicities and commonly fail to convey the predictive power of their findings. This article presents a Bayesian probabilistic modeling framework for the GLCM as a multivariate object as well as describes its application within a cancer detection context based on computed tomography. The methodology, which circumvents processing steps and avoids evaluations of reductive and highly correlated feature sets, uses latent Gaussian Markov random field structure to characterize spatial dependencies among GLCM cells and facilitates classification via predictive probability. Correctly predicting the underlying pathology of 81% of the adrenal lesions in our case study, the proposed method outperformed current practices which achieved a maximum accuracy of only 59%. Simulations and theory are presented to further elucidate this comparison as well as ascertain the utility of applying multivariate Gaussian spatial processes to GLCM objects.     

Bayesian inference for Birnbaum–Saunders distribution and its generalization

We present a Bayesian approach for parameter inference of the Birnbaum–Saunders distribution [Birnbaum ZW, Saunders SC. A new family of life distributions. J Appl Probab. 1969;6:319–327], as well as the generalized Birnbaum–Saunders distribution developed by Owen [A new three-parameter extension to the Birnbaum–Saunders distribution. IEEE Trans Reliab. 2006;55:475–479], in the presence of random right-censored data. To handle the instance of commonly occurred censored observations, we utilize the data augmentation technique [Tanner MA, Wong WH. The calculation of posterior distributions by data augmentation. J Amer Statist Assoc. 1987;82(398):528–540] to circumvent the arduous expressions involving the censored data in posterior inferences. Simulation studies are carried out to assess performance of these methods under different parameter values, with small and large sample sizes, as well as various degrees of censoring. Two real data are analysed for illustrative purpose.     

Evaluation of an avatar-based training program to promote suicide prevention awareness in a college setting

Objective: Training programs exist that prepare college students, faculty, and staff to identify and support students potentially at risk for suicide. Kognito is an online program that trains users through simulated interactions with virtual humans. This study evaluated Kognito's effectiveness in preparing users to intervene with at-risk students. Participants: Training was completed by 2,727 university students, faculty, and staff from April, 2014 through September, 2015. Methods: Voluntary and mandatory participants at a land-grant university completed Kognito modules designed for higher education, along with pre- and post-assessments. Results: All modules produced significant gains in reported Preparedness, Likelihood, and Self-Efficacy in intervening with troubled students. Despite initial disparities in reported abilities, after training participants reported being similarly capable of assisting at-risk students, including LGBTQ and veteran students. Conclusions: Kognito training appears to be effective, on a large scale, in educating users to act in a facilitative role for at-risk college students.     

Transformational leadership and performance outcomes: Analyses of multiple mediation pathways

Transformational leadership (TFL) has been shown to affect employees' job performance, and the literature offers a large variety of explanatory processes. Integrating the diverse literature related to the mechanisms that mediate the TFL-performance relationship, the current study identified five core mechanisms—affective, motivational, identification, social exchange, and justice enhancement—that are consistent with established social and psychological theories. Meta-analysis involving > 600 samples was conducted to test these mechanisms. General support was found for each of the five mechanisms. The findings showed that TFL was related to variables that represented these mechanisms, which in turn were associated with non-self-report measures of employees' task performance, citizenship behavior, and innovative behavior. An integrative model was further proposed and tested to show the central role of leader-member exchange in the relationships between TFL, other mediating variables, and performance outcomes. This study contributes to the literature by strengthening researchers' theoretical understanding of the major social and psychological processes by which transformational leaders promote followers' job performance.     

Interaction Effects of Gender,SES, and Race‐Ethnicity on Postsecondary Educational Choices of U.S. Students

The authors present data for a subsample of the National Education Longitudinal Study of 1988 (NELS:88; 1996). All participants in the study had attended a postsecondary institution within 2 years of graduation from high school and had selected a field of study. Educational choices were categorized by predominant Holland types (e.g., Realistic, Social, Conventional). There was a 3‐way Gender × SES × Race‐Ethnicity interaction. Race‐ethnicity effects were strongest for men at lower SES levels and weakest for women at high SES levels. The nature of gender and SES effects differed across racial‐ethnic groups.     

Public participation in infrastructure and construction projects in China: From an EIA-based to a whole-cycle process

Many governments world-wide are increasingly encouraging the involvement of interested individuals, groups and organisations in their public infrastructure and construction (PIC) projects as a means of improving the openness, transparency and accountability of the decision-making process and help improve the projects’ long-term viability and benefits to the community. In China, however, the current participatory mechanism at the project level exists only as part of the environmental impact assessment (EIA) process. With an increasing demand for PIC projects and social equality in China, this suggests a need to bring the participatory process into line with international practice.The aim of this paper, therefore, is to identify the weaknesses of EIA-based public participation in China and the means by which it may be improved for the whole lifecycle of PIC schemes. To do this, the results of a series of interviews with a diverse group of experts is reported which analyse the nature and extent of existing problems of public participation in EIA and suggestions for improvement. These indicate that the current level of participation in PIC projects is quite limited, particularly in the crucial earlier stages, primarily due to traditional culture and values, uneven progress in the adoption of participatory mechanisms, the risk of not meeting targets and lack of confidence in public competence. Finally, a process flowchart is proposed to guide construction practitioners and the community in general.     

Affluence,Feelings of Stress,and Well-being

Data from the Gallup World Poll highlighted the differential relations between perceived stress, well-being, and wealth at the individual- versus nation-level. At the nation level, stress was a distinct concept from negative affect (NA). It correlated positively with well-being (positive affect, life satisfaction, and domain satisfaction) and wealth (as measured by income, gross domestic product, and modern conveniences). In contrast, NA correlated inversely with well-being and income. Although similar to NA at the individual level, stress showed weaker negative relations with well-being than NA did. In sum, nation-level stress and NA were related in the opposite direction to wealth (and poverty), well-being, and life expectancy. Furthermore, the concept of stress differed at the individual and nation levels. For the former, stress appeared to be purely a negative marker of affective well-being (albeit weaker than other discrete negative emotions); for the latter, it appeared to reflect lifestyle differences that were strongly associated with wealth, and with affective and cognitive well-being to a smaller degree.     

Weighted stochastic block model

Statistical Methods & Applications - We propose a weighted stochastic block model (WSBM) which extends the stochastic block model to the important case in which edges are weighted. We address...     

Impacts of financial crisis on social engagement in Hong Kong

While a financial crisis must afflict people financially, its impacts on people's social life are unclear. Essentially, different theories expect different impacts of the financial crisis on people's social engagement. The present study thereby clarifies the effect by examining the experienced impact of the crisis on social engagement, in terms of participation in voluntary association and caring for acquaintances. Data for the study came from a survey of 1170 Hong Kong Chinese adults. Results show that the experienced impact tended to raise the participation, which in turn appeared to encourage the caring. These results support the functional explanation, which holds that the fiscal crisis generates a need for functions of voluntary associations. Meanwhile, the results are at odds with the resource thesis, which expects that the crisis would deprive resources required for social engagement. The results imply that the financial crisis can be a lever to strengthen social engagement.