Statistical modeling for Bayesian extrapolation of adult clinical trial information in pediatric drug evaluation

Children represent a large underserved population of “therapeutic orphans,” as an estimated 80% of children are treated off‐label. However, pediatric drug development often faces substantial challenges, including economic, logistical, technical, and ethical barriers, among others. Among many efforts trying to remove these barriers, increased recent attention has been paid to extrapolation; that is, the leveraging of available data from adults or older age groups to draw conclusions for the pediatric population. The Bayesian statistical paradigm is natural in this setting, as it permits the combining (or “borrowing”) of information across disparate sources, such as the adult and pediatric data. In this paper, authored by the pediatric subteam of the Drug Information Association Bayesian Scientific Working Group and Adaptive Design Working Group, we develop, illustrate, and provide suggestions on Bayesian statistical methods that could be used to design improved pediatric development programs that use all available information in the most efficient manner. A variety of relevant Bayesian approaches are described, several of which are illustrated through 2 case studies: extrapolating adult efficacy data to expand the labeling for Remicade to include pediatric ulcerative colitis and extrapolating adult exposure‐response information for antiepileptic drugs to pediatrics.     

Improving the detection of unusual observations in high‐dimensional settings

Multivariate control charts are used to monitor stochastic processes for changes and unusual observations. Hotelling's T² statistic is calculated for each new observation and an out‐of‐control signal is issued if it goes beyond the control limits. However, this classical approach becomes unreliable as the number of variables p approaches the number of observations n, and impossible when p exceeds n. In this paper, we devise an improvement to the monitoring procedure in high‐dimensional settings. We regularise the covariance matrix to estimate the baseline parameter and incorporate a leave‐one‐out re‐sampling approach to estimate the empirical distribution of future observations. An extensive simulation study demonstrates that the new method outperforms the classical Hotelling T² approach in power, and maintains appropriate false positive rates. We demonstrate the utility of the method using a set of quality control samples collected to monitor a gas chromatography–mass spectrometry apparatus over a period of 67 days.     

Pricing power options with a generalized jump diffusion

In this article, the valuation of power option is investigated when the dynamic of the stock price is governed by a generalized jump-diffusion Markov-modulated model. The systematic risk is characterized by the diffusion part, and the non systematic risk is characterized by the pure jump process. The jumps are described by a generalized renewal process with generalized jump amplitude. By introducing NASDAQ Index Model, their risk premium is identified respectively. A risk-neutral measure is identified by employing Esscher transform with two families of parameters, which represent the two parts risk premium. In this article, the non systematic risk premium is considered, based on which the price of power option is studied under the generalized jump-diffusion Markov-modulated model. In the case of a special renewal process with log double exponential jump amplitude, the accurate expressions for the Esscher parameters and the pricing formula are provided. By numerical simulation, the influence of the non systematic risk’s price and the index of the power options on the price of the option is depicted.     

Extended scaled prediction variance optimality for modified central composite design

Robust parameter designs (RPDs) enable the experimenter to discover how to modify the design of the product to minimize the effect due to variation from noise sources. The aim of this article is to show how this amount of work can be reduced under modified central composite design (MCCD). We propose a measure of extended scaled prediction variance (ESPV) for evaluation of RPDs on MCCD. Using these measures, we show that we can check the error or bias associated with estimating the model parameters and suggest the values of α recommended for MCCS under minimum ESPV.     

The performance of model averaged tail area confidence intervals

We investigate the exact coverage and expected length properties of the model averaged tail area (MATA) confidence interval proposed by Turek and Fletcher, CSDA, 2012, in the context of two nested, normal linear regression models. The simpler model is obtained by applying a single linear constraint on the regression parameter vector of the full model. For given length of response vector and nominal coverage of the MATA confidence interval, we consider all possible models of this type and all possible true parameter values, together with a wide class of design matrices and parameters of interest. Our results show that, while not ideal, MATA confidence intervals perform surprisingly well in our regression scenario, provided that we use the minimum weight within the class of weights that we consider on the simpler model.     

我国异质性产业体系低碳化发展的实现路径及其影响因素

本文建立了一个异质性产业体系低碳化发展路径选择的分析框架,通过超越对数形式的随机前沿生产函数,测算了我国29个省区产业体系生产技术及其效率和生产规模效率,以及能源使用技术及其效率和碳减排技术及其效率,并针对不同类型产业体系的低碳化发展提出政策建议.结果表明,我国异质性产业体系可以通过不同的结构升级和技术进步的选择形成适合于自身产业体系特征的低碳化发展路径.     

我国高校扩招后办学效率和生产率的变化

高校扩招时期我国高等教育的快速发展是否属于“粗放型”？高校办学规模减速后是否逐步走上了内涵式发展道路？本文以教育部直属高校为分析对象,采用DEA-Malmquist指数分析并回答这两个问题.研究发现,高校扩招至2006年之前,教育部直属高校的快速发展属于有质量的增长,这一时期全要素生产率的大幅提升与技术进步和技术效率改善都有关系,但技术进步的贡献更大.2006年之后,由于技术进步的促进作用逐步消失,以及追赶效应的“自然衰老”,生产率的增长出现明显的放缓.但是,如果考虑有质量的产出,2006年后技术效率的下降幅度并不明显,这在一定程度上验证了内涵式发展目标的成效.     

基于化学反应算法的鲜活农产品配送路径优化

文章通过引入时间价格因子考虑在鲜活农产品配送过程的损耗并结合运输成本和惩罚成本构建数学模型.从实际的运用环境出发,考虑到未在期望获得时间内达到运输地点的成本消耗,并且随着时间的推移,鲜活农产品本身也有成本损耗构建目标函数.根据该模型的特点设计化学反应的最小单元分子结构和算法步骤.运用化学反应算法可以很好地解决模型算法过早收敛于局部最优问题.通过实例验证了模型和算法的有效性和科学性.     

企业内部控制有效性影响因素的实证

作为公司治理的核心,董事会负责公司的重大决策和对管理层的监督,对公司内部控制的设计与实施效果有着重要影响.文章以2012-2014年国内A股上市公司为研究样本,实证检验了董事会治理特征对公司内部控制有效性的影响.检验结果表明,上市公司董事会的规模与会议次数与内部控制有效性无关;独立董事比例、审计委员会的设立、董事持股比例与内部控制有效性正相关;董事长与CEO二职合一与内部控制有效性负相关.     

Calculable Power: A Case Study of IMF Quotas and Voting Rights Reform*

Voting procedure is an important mechanism for public choice in collective bodies such as international organizations. This paper measures and compares IMF member countries’ voting power before the 2008 reform and after the 2010 reform on the basis of datasets on IMF quotas and voting rights distribution provided by IMF. Our study verifies that IMF’s quotas and voting rights reforms do help to reduce the voting power gap among member countries. The 2008 and 2010 reforms produce a greater improvement in emerging members’ voting power under the 70 percent majority rule than the 85 percent rule; the 70 percent majority rule means the United States would lose its absolute veto. Moreover, the paper disproves the underlying assumption that regards a member’s voting power as proportional to its voting rights. Countries with different amounts of voting rights can still have the same voting power.