Probability of success for phase III after exploratory biomarker analysis in phase II

The probability of success or average power describes the potential of a future trial by weighting the power with a probability distribution of the treatment effect. The treatment effect estimate from a previous trial can be used to define such a distribution. During the development of targeted therapies, it is common practice to look for predictive biomarkers. The consequence is that the trial population for phase III is often selected on the basis of the most extreme result from phase II biomarker subgroup analyses. In such a case, there is a tendency to overestimate the treatment effect. We investigate whether the overestimation of the treatment effect estimate from phase II is transformed into a positive bias for the probability of success for phase III. We simulate a phase II/III development program for targeted therapies. This simulation allows to investigate selection probabilities and allows to compare the estimated with the true probability of success. We consider the estimated probability of success with and without subgroup selection. Depending on the true treatment effects, there is a negative bias without selection because of the weighting by the phase II distribution. In comparison, selection increases the estimated probability of success. Thus, selection does not lead to a bias in probability of success if underestimation due to the phase II distribution and overestimation due to selection cancel each other out. We recommend to perform similar simulations in practice to get the necessary information about the risk and chances associated with such subgroup selection designs.     

On the detection of changes in autoregressive time series,II. Resampling procedures

We study an autoregressive time series model with a possible change in the regression parameters. Approximations to the critical values for change-point tests are obtained through various bootstrapping methods. Theoretical results show that the bootstrapping procedures have the same limiting behavior as their asymptotic counterparts discussed in Hušková et al. [2007. On the detection of changes in autoregressive time series, I. Asymptotics. J. Statist. Plann. Inference 137, 1243–1259]. In fact, a small simulation study illustrates that the bootstrap tests behave better than the original asymptotic tests if performance is measured by the α$\alpha$- and β$\beta$-errors, respectively.     

吸收能力、专用机制与研发边界开放度

内容提要：在开放创新背景下,吸收能力、专用机制对企业研发边界开放度决策具有重要影响;本文运用资源基础、产权以及期权与交易成本理论构建了一个关于吸收能力、专用机制和相关控制变量对研发边界开放度决策影响的综合解释框架,提出了四个理论假设;根据现有文献样本,运用元分析方法,对假设进行了检验;最后,指出了进一步研究方向。     

Change of origin and scale in ratio and difference methods of estimation in sampling

This paper discusses two estimators of the mean of a finite population based on a simple random sample from it, when supplementary information on a variable positively correlated with the variable of interest is available. Simultaneous reductions in absolute bias and mean square error of the estimator are seen as compared with those of the traditional estimator in the ratio method of estimation. The suggested estimators are simple for computation and there is no appreciable increase in the cost as well.     

Fully efficient estimation of coefficients of correlation in the presence of imputed survey data

Marginal imputation, that consists of imputing items separately, generally leads to biased estimators of bivariate parameters such as finite population coefficients of correlation. To overcome this problem, two main approaches have been considered in the literature: the first consists of using customary imputation methods such as random hot‐deck imputation and adjusting for the bias at the estimation stage. This approach was studied in Skinner & Rao 2002 . In this paper, we extend the results of Skinner & Rao 2002 to the case of arbitrary sampling designs and three variants of random hot‐deck imputation. The second approach consists of using an imputation method, which preserves the relationship between variables. Shao & Wang 2002 proposed a joint random regression imputation procedure that succeeds in preserving the relationships between two study variables. One drawback of the Shao–Wang procedure is that it suffers from an additional variability (called the imputation variance) due to the random selection of residuals, resulting in potentially inefficient estimators. Following Chauvet, Deville, & Haziza 2011 , we propose a fully efficient version of the Shao–Wang procedure that preserves the relationship between two study variables, while virtually eliminating the imputation variance. Results of a simulation study support our findings. An application using data from the Workplace and Employees Survey is also presented. The Canadian Journal of Statistics 40: 124–149; 2012 © 2011 Statistical Society of Canada     

Functional Analysis of Variance,Discriminant Analysis,and Clustering in a Manifold of Elastic Curves

We develop functional data analysis techniques using the differential geometry of a manifold of smooth elastic functions on an interval in which the functions are represented by a log-speed function and an angle function. The manifold's geometry provides a method for computing a sample mean function and principal components on tangent spaces. Using tangent principal component analysis, we estimate probability models for functional data and apply them to functional analysis of variance, discriminant analysis, and clustering. We demonstrate these tasks using a collection of growth curves from children from ages 1–18.     

Joint distribution of rises,falls, and number of runs in random sequences

By using the matrix formulation of the two-step approach to the distributions of runs, a recursive relation and an explicit expression are derived for the generating function of the joint distribution of rises and falls for multivariate random sequences in terms of generating functions of individual letters, from which the generating functions of the joint distribution of rises, falls, and number of runs are obtained. An explicit formula for the joint distribution of rises and falls with arbitrary specification is also obtained.     

Estimation of Pr{yp > max(y1, …, yp-1)}: Predictive approach in exponential case

The structural-inference approach to predictive distributions is used to derive the estimator of P = Pr{Y_p > max(Y₁, …, Y_p-₁)} when the independent random variables Y₁, …, Y_p follow exponential distributions with unequal location parameters and equal scale parameters. The result is Equation (4.6).     

城市化发展中的产业升级:集聚推动、溢出效应与空间衰减——基于西北地区的空间计量

城市化和产业发展进程中均呈现集聚经济特征,城市化发展中的要素集聚对集聚形态下的产业层次提升具有明显的推动。基于2005—2012年西北地区30个城市的面板数据,利用空间计量方法分析了城市化发展对产业升级的推动效应。研究结果表明,西北地区城市化发展带来的要素集聚对产业升级具有明显的正向推动,同时城市化集聚对相邻城市的产业升级存在空间溢出效应,利用空间阈值权重矩阵进一步分析后发现,600km以内时城市化发展对产业升级存在显著的正向空间溢出,但溢出效应随空间距离的增长呈现下降趋势,超出600km之后转为负向空间溢出,同时城市化发展中其他结构性因素对产业升级存在空间效应,空间效应方向和趋势由于各结构因素的特征而有所差异。基于上述实证研究,提出了相应的政策建议。     

Properties of maximum likelihood estimators of variance components in the one-way classification,balanced data

We studied properties of maximum likelihood estimators (MLEs) of the variance components obtained from balanced data of the one-way classification. Exact and asymptotic expected values and variances of these MLEs were derived under the usual normality assumptions. Numerical studies illustrate these expected values and variances, and also illustrate the probability of obtaining a negative solution to the maximum likelihood (ML) equation for the between-class variance component. Simulations were used to study the robustness of the ML estimators under non-normal distributions.     

Basic structure of the asymptotic theory in dynamic nonlineaerco nometric models, part i: consistency and approximation concepts

This is the first of two papers that provide an expository discussion of the basic structure of the asymptotic theory of M-estimators in dynamic nonlinear models and a revlew of the literature. In this paper we discuss consistency,uniform laws of large numbers and develop a new framework for laws of large numbers for dependent and heterogeneous processes, encompassing the theory of stochastically stable as well as near epoch dependent processes. This framework results in simplified catalogues of sufficient conditions for consistency. The second paper, Potscher and Prucha (1990b), deals with asymptotic distribution theory.     

陕西省小城镇规模布局与经济发展要素关系的数量分析

文章应用双对数虚拟变量模型,研究了陕西省小城镇的发展规模、地域差异与经济要素之间的数量关系,分析了陕西省小城镇发展过程中存在的问题,并为陕西省政府制定小城镇规模布局的发展战略和政策提供了相关依据。     

准入制度改革、同业竞争与银行业市场进入决策机制升级

为了研究我国银行业市场准入制度改革对银行市场进入决策机制的影响和检验银行间差异化竞争战略的实施成效,本文基于中小股份制商业银行分支数据构建静态离散博弈的均衡结构模型还原银行市场进入过程中的战略互动,并重点考察不同垄断地位银行间非对称的竞争壁垒效应。鉴于多重Nash均衡引起的估计不一致问题,分别使用条件矩不等式和子样本模拟技术识别与估计模型参数的置信区间,并进一步设计反事实分析和分类比较分析。研究发现,我国银行业准入制度放松显著推动了市场进入决策机制升级,使其不仅取决于银行内部优势和市场区位,也受制于对手决策及其构建的品牌、规模经济等非对称竞争壁垒;银行边际利润实现从第二产业向第三产业转移,当前银行业的“壁龛市场”战略占优于“跟随”战略。