Modifications of sequential designs in bioequivalence trials

Bioequivalence (BE) studies are designed to show that two formulations of one drug are equivalent and they play an important role in drug development. When in a design stage, it is possible that there is a high degree of uncertainty on variability of the formulations and the actual performance of the test versus reference formulation. Therefore, an interim look may be desirable to stop the study if there is no chance of claiming BE at the end (futility), or claim BE if evidence is sufficient (efficacy), or adjust the sample size. Sequential design approaches specially for BE studies have been proposed previously in publications. We applied modification to the existing methods focusing on simplified multiplicity adjustment and futility stopping. We name our method modified sequential design for BE studies (MSDBE). Simulation results demonstrate comparable performance between MSDBE and the original published methods while MSDBE offers more transparency and better applicability. The R package MSDBE is available at https://sites.google.com/site/modsdbe/ . Copyright © 2015 John Wiley & Sons, Ltd.     

Analyzing multiple vector autoregressions through matrix-variate normal distribution with two covariance matrices

Abstract

This article proposes a new approach to analyze multiple vector autoregressive (VAR) models that render us a newly constructed matrix autoregressive (MtAR) model based on a matrix-variate normal distribution with two covariance matrices. The MtAR is a generalization of VAR models where the two covariance matrices allow the extension of MtAR to a structural MtAR analysis. The proposed MtAR can also incorporate different lag orders across VAR systems that provide more flexibility to the model. The estimation results from a simulation study and an empirical study on macroeconomic application show favorable performance of our proposed models and method.     

Security Investment in Contagious Networks

Security of the systems is normally interdependent in such a way that security risks of one part affect other parts and threats spread through the vulnerable links in the network. So, the risks of the systems can be mitigated through investments in the security of interconnecting links. This article takes an innovative look at the problem of security investment of nodes on their vulnerable links in a given contagious network as a game‐theoretic model that can be applied to a variety of applications including information systems. In the proposed game model, each node computes its corresponding risk based on the value of its assets, vulnerabilities, and threats to determine the optimum level of security investments on its external links respecting its limited budget. Furthermore, direct and indirect nonlinear influences of a node's security investment on the risks of other nodes are considered. The existence and uniqueness of the game's Nash equilibrium in the proposed game are also proved. Further analysis of the model in a practical case revealed that taking advantage of the investment effects of other players, perfectly rational players (i.e., those who use the utility function of the proposed game model) make more cost‐effective decisions than selfish nonrational or semirational players.     

Reducing sample size needed for cox-proportional hazards model analysis using more efficient sampling method

Abstract

In general, survival data are time-to-event data, such as time to death, time to appearance of a tumor, or time to recurrence of a disease. Models for survival data have frequently been based on the proportional hazards model, proposed by Cox. The Cox model has intensive application in the field of social, medical, behavioral and public health sciences. In this paper we propose a more efficient sampling method of recruiting subjects for survival analysis. We propose using a Moving Extreme Ranked Set Sampling (MERSS) scheme with ranking based on an easy-to-evaluate baseline auxiliary variable known to be associated with survival time. This paper demonstrates that this approach provides a more powerful testing procedure as well as a more efficient estimate of hazard ratio than that based on simple random sampling (SRS). Theoretical derivation and simulation studies are provided. The Iowa 65+ Rural study data are used to illustrate the methods developed in this paper.     

Hierarchical Bayesian Modeling of Post-Earthquake Ignition Probabilities Considering Inter-Earthquake Heterogeneity

Post-earthquake fires are high-consequence events with extensive damage potential. They are also low-frequency events, so their nature remains underinvestigated. One difficulty in modeling post-earthquake ignition probabilities is reducing the model uncertainty attributed to the scarce source data. The data scarcity problem has been resolved by pooling the data indiscriminately collected from multiple earthquakes. However, this approach neglects the inter-earthquake heterogeneity in the regional and seasonal characteristics, which is indispensable for risk assessment of future post-earthquake fires. Thus, the present study analyzes the post-earthquake ignition probabilities of five major earthquakes in Japan from 1995 to 2016 (1995 Kobe, 2003 Tokachi-oki, 2004 Niigata–Chuetsu, 2011 Tohoku, and 2016 Kumamoto earthquakes) by a hierarchical Bayesian approach. As the ignition causes of earthquakes share a certain commonality, common prior distributions were assigned to the parameters, and samples were drawn from the target posterior distribution of the parameters by a Markov chain Monte Carlo simulation. The results of the hierarchical model were comparatively analyzed with those of pooled and independent models. Although the pooled and hierarchical models were both robust in comparison with the independent model, the pooled model underestimated the ignition probabilities of earthquakes with few data samples. Among the tested models, the hierarchical model was least affected by the source-to-source variability in the data. The heterogeneity of post-earthquake ignitions with different regional and seasonal characteristics has long been desired in the modeling of post-earthquake ignition probabilities but has not been properly considered in the existing approaches. The presented hierarchical Bayesian approach provides a systematic and rational framework to effectively cope with this problem, which consequently enhances the statistical reliability and stability of estimating post-earthquake ignition probabilities.     

A New Methodology for Before–After Safety Assessment Using Survival Analysis and Longitudinal Data

The widely used empirical Bayes (EB) and full Bayes (FB) methods for before–after safety assessment are sometimes limited because of the extensive data needs from additional reference sites. To address this issue, this study proposes a novel before–after safety evaluation methodology based on survival analysis and longitudinal data as an alternative to the EB/FB method. A Bayesian survival analysis (SARE) model with a random effect term to address the unobserved heterogeneity across sites is developed. The proposed survival analysis method is validated through a simulation study before its application. Subsequently, the SARE model is developed in a case study to evaluate the safety effectiveness of a recent red‐light‐running photo enforcement program in New Jersey. As demonstrated in the simulation and the case study, the survival analysis can provide valid estimates using only data from treated sites, and thus its results will not be affected by the selection of defective or insufficient reference sites. In addition, the proposed approach can take into account the censored data generated due to the transition from the before period to the after period, which has not been previously explored in the literature. Using individual crashes as units of analysis, survival analysis can incorporate longitudinal covariates such as the traffic volume and weather variation, and thus can explicitly account for the potential temporal heterogeneity.     

Juvenile Delinquency Under Conditions of Rapid Social Change

Increased juvenile delinquency can be seen as an indicator for a deteriorating social fabric under conditions of rapid social change. Criminological theories suggest, however, that such conditions do not per se produce delinquency: They force youth into prodelinquent leisure activities with peers, leading to an endorsement of delinquent behavior and offering the infrastructure for it. Resources acquired in family and public life, however, may prevent youth from drifting into such prodelinquent leisure activities and indirectly from delinquent behavior. Empirical tests of these hypotheses have to employ simultaneous analyses of societal-level and individual-level data. On the basis of an international youth study, the paper undertakes such an analysis: In the years 1992–95, data from 42 independent samples of seventh graders from East and West Germany, Poland, Russia, Bulgaria, Slovakia, Hungary, Czechia, and Greece were surveyed. Data on deviant school behavior, delinquent drift, nurturant parenting, and subjective feelings of justice in public were obtained from 7282 thirteen- to fourteen-year-olds. Processes of rapid social change were incorporated as data on changes in GNP in the years proceeding the surveys. Analyses show that delinquent drift is a valid predictor of deviant school behavior only on the individual level. The extent to which adolescents engage in prodelinquent peer activities depends more on the cultural context in which adolescents live than on their personal experience in the family and in public. Nurturant parenting does, however, covary negatively with deviant school behavior irrespective of level of analysis.     

‘There Oughtta Be a Law Against Bitches’: Masculinity Lessons in Police Academy Training

This article draws on participant observation in a law enforcement academy to demonstrate how a hidden curriculum encourages aspects of hegemonic masculinity among recruits. Academy training teaches female and male recruits that masculinity is an essential requirement for the practice of policing and that women do not belong. By watching and learning from instructors and each other, male students developed a form of masculinity that (1) excluded women students and exaggerated differences between them and men; and (2) denigrated women in general. Thus, the masculinity that is characteristic of police forces and is partly responsible for women’s low representation on them is not produced exclusively on the job, but is taught in police academies as a subtext of professional socialization.     

Linguists and other animals

Book reviewed in this article:
Joan Dunayer, Animal Equality: Language and Liberation     

三维实体设计与工程制图课程的改革

三维实体设计是工程设计的必然趋势,设计方法的变革导致企业对人才的新需求,也给传统的工程制图课程体系带来了巨大的冲击。改革与现代生产和人才需求不相适应的教学内容,建立以三维设计为主线,以培养创新思维和创新能力为目标的工程制图新体系,是工程制图课程改革的方向。