Inference and Decision Making for 21st-Century Drug Development and Approval

ABSTRACT

The cost and time of pharmaceutical drug development continue to grow at rates that many say are unsustainable. These trends have enormous impact on what treatments get to patients, when they get them and how they are used. The statistical framework for supporting decisions in regulated clinical development of new medicines has followed a traditional path of frequentist methodology. Trials using hypothesis tests of “no treatment effect” are done routinely, and the p-value < 0.05 is often the determinant of what constitutes a “successful” trial. Many drugs fail in clinical development, adding to the cost of new medicines, and some evidence points blame at the deficiencies of the frequentist paradigm. An unknown number effective medicines may have been abandoned because trials were declared “unsuccessful” due to a p-value exceeding 0.05. Recently, the Bayesian paradigm has shown utility in the clinical drug development process for its probability-based inference. We argue for a Bayesian approach that employs data from other trials as a “prior” for Phase 3 trials so that synthesized evidence across trials can be utilized to compute probability statements that are valuable for understanding the magnitude of treatment effect. Such a Bayesian paradigm provides a promising framework for improving statistical inference and regulatory decision making.     

Inference for the measurement of poverty in the presence of a stochastic weighting variable

Empirical applications of poverty measurement often have to deal with a stochastic weighting variable such as household size. Within the framework of a bivariate distribution function defined over income and weight, I derive the limiting distributions of the decomposable poverty measures and of the ordinates of stochastic dominance curves. The poverty line is allowed to depend on the income distribution. It is shown how the results can be used to test hypotheses concerning changes in poverty. The inference procedures are briefly illustrated using Belgian data. An erratum to this article can be found at     

统计执法的博弈分析

针对目前中国统计数据失真相当严重并引起社会各界普遍关注的现象，运用博弈论作为分析工具，引入重复博弈研究了统计执法中数据报方与查方的利益冲突关系，从统计执法的角度揭示了统计数据失真的主要原因，并提出了相应的五项对策。     

Empirical Non-Parametric Control Charts: Estimation Effects and Corrections

Owing to the extreme quantiles involved, standard control charts are very sensitive to the effects of parameter estimation and non-normality. More general parametric charts have been devised to deal with the latter complication and corrections have been derived to compensate for the estimation step, both under normal and parametric models. The resulting procedures offer a satisfactory solution over a broad range of underlying distributions. However, situations do occur where even such a large model is inadequate and nothing remains but to consider non- parametric charts. In principle, these form ideal solutions, but the problem is that huge sample sizes are required for the estimation step. Otherwise the resulting stochastic error is so large that the chart is very unstable, a disadvantage that seems to outweigh the advantage of avoiding the model error from the parametric case. Here we analyse under what conditions non-parametric charts actually become feasible alternatives for their parametric counterparts. In particular, corrected versions are suggested for which a possible change point is reached at sample sizes that are markedly less huge (but still larger than the customary range). These corrections serve to control the behaviour during in-control (markedly wrong outcomes of the estimates only occur sufficiently rarely). The price for this protection will clearly be some loss of detection power during out-of-control. A change point comes in view as soon as this loss can be made sufficiently small.     

高校教师教书育人的途径和方法研究

本文在肯定教师在高等学校对学生传授知识、培养能力方面的作用基础上,指出教书育人是教师的神圣职责并提出教师教书育人的重要途径和方法。     

企业的合约经济理论探索和统计检验

对企业本质的认识是微观经济学中的一个重要问题,其对中国的国企改革有着重要意义。本文中,我们对企业的合约本质进行了经济理论探索和统计检验,并突出关注企业的激励合约问题。     

统计调查课程的现状与调整思路

文章从统计调查课程设置的现状出发,介绍了当前随着社会经济的发展和统计调查方法体系的改革,统计调查理论体系以及统计调查课程设置的不足,叙述了统计调查课程调整的思路。要实施这个思路,必须重视统计调查对象内容的变化,并注重借鉴国外成熟的经验。为适应形势的发展,随着现行统计调查方法体系的调整与完善,对统计调查课程也要作相应的调整。     

Bayesian analysis of directed graphs data with applications to social networks

Summary.  A fully Bayesian analysis of directed graphs, with particular emphasis on applica- tions in social networks, is explored. The model is capable of incorporating the effects of covariates, within and between block ties and multiple responses. Inference is straightforward by using software that is based on Markov chain Monte Carlo methods. Examples are provided which highlight the variety of data sets that can be entertained and the ease with which they can be analysed.     

指数分析中多种方法的结合运用

指数分析法在经济分析的各个领域里已得到广泛的应用。但只用单一方法分析问题往往不够全面、深入。本文以工业劳动生产率的分析为例,从三个方面,多角度、多层次、比较系统地阐述了指数分析中独具特色的分析手法。     

Inside two commercially available statistical expert systems

A decade of research into the applications of artificial intelligence in statistics has finally resulted in the appearance of commercially available statistical expert systems. This paper takes a closer look at two of these systems, which are now commercially available on microcomputers, and shows what knowledge they actually contain and how they operate. It is concluded that although the technology and concepts that drive these systems could still benefit from further improvement, the real challenge lies in defining and constructing the statistical knowledge and strategy that should be incorporated and in presenting the results to the user's full advantage.