Bayesian sequential analysis for multiple-arm clinical trials

Use of full Bayesian decision-theoretic approaches to obtain optimal stopping rules for clinical trial designs typically requires the use of Backward Induction. However, the implementation of Backward Induction, apart from simple trial designs, is generally impossible due to analytical and computational difficulties. In this paper we present a numerical approximation of Backward Induction in a multiple-arm clinical trial design comparing k experimental treatments with a standard treatment where patient response is binary. We propose a novel stopping rule, denoted by τ ^p , as an approximation of the optimal stopping rule, using the optimal stopping rule of a single-arm clinical trial obtained by Backward Induction. We then present an example of a double-arm (k=2) clinical trial where we use a simulation-based algorithm together with τ ^p to estimate the expected utility of continuing and compare our estimates with exact values obtained by an implementation of Backward Induction. For trials with more than two treatment arms, we evaluate τ ^p by studying its operating characteristics in a three-arm trial example. Results from these examples show that our approximate trial design has attractive properties and hence offers a relevant solution to the problem posed by Backward Induction.     

一类新的数据变换及其对提高灰预测精度的有效性研究

提出了经过非负函数cg(x)+d变换来提高GM(1,1)模型的预测精度,并从理论上证明,这类变换为级比偏差压缩变换,保证了数据变换后的序列有非负上凹的特性,还原后的误差不会增大等性质,并通过实例对比说明了这种变换的有效性。     

The LASSO Method for Bilinear Time Series Models

In this article we propose a method called GLLS for the fitting of bilinear time series models. The GLLS procedure is the combination of the LASSO method, the generalized cross-validation method, the least angle regression method, and the stepwise regression method. Compared with the traditional methods such as the repeated residual method and the genetic algorithm, GLLS has the advantage of shrinking the coefficients of the models and saving the computational time. The Monte Carlo simulation studies and a real data example are reported to assess the performance of the proposed GLLS method.     

Bayesian randomized clinical trials: A decision‐theoretic sequential design

The authors propose a Bayesian decision‐theoretic framework justifying randomization in clinical trials. Noting that the decision maker is often unable or unwilling to specify a unique utility function, they develop a sequential myopic design that includes randomization justified by the consideration of a set of utility functions. Randomization is introduced over all nondominated treatments, allowing for interim removal of treatments and early stopping. The authors illustrate their approach in the context of a study to find the optimal dose of pegylated interferon for platinum resistant ovarian cancer. They also develop an algorithm to implement their methodology in a phase II clinical trial comparing several competing experimental treatments.     

东部地区物流业竞争力影响要素研究

综合考虑要素投入与物流业竞争力水平之间的关系,根据2007~2013年我国东部11省市物流数据,构建物流业竞争力固定效应回归计量模型,分析要素投入包括科技人员、固定资产投资、产业结构对物流业竞争力的影响程度,运用逐步回归对其显著因素进行识别。结果表明,固定资产投资与物流业竞争力呈现正相关,科技人员和第三产业发展对物流业竞争力的提升呈现负相关。因此东部地区在积极投资物流基础设施的同时亟需走以创新型人力资本为主体,以产业结构优化为方向的自主创新道路。     

农村卫生室收入情况调查与实证分析--以湖北省松滋市为例

村卫生室是农村三级医疗预防保健网的网底,承担着为农村居民提供基本公共卫生服务与疾病初级诊治的职责。村卫生室的收入情况直接影响到农村医生的收入水平与工作积极性。而村卫生室的收入受到村卫生室门诊人数、经营面积、村医人数等因素的影响。通过对湖北省松滋市259所村卫生室年收入情况进行实地调查,运用计量分析方法分析了影响村卫生室年收入的主要因素。     

A finite capacity material requirements planning system

In a discrete parts manufacturing environment, material requirement planning (MRP) is carried out without considering the manufacturing resource capacity. As a result, during implementation, adjustments in planned orders may become necessary. This paper presents a finite capacity material requirements planning algorithm (FCMRP) to obtain capacity-based production plans. These plans need no costly adjustments to satisfy the capacity constraints. Performance of the FCMRP system, when studied through a set of test examples, has been found to be superior to the existing MRP system.     

Forward and backward stepping in variable selection

For stepwise regression and discriminant analysis the parameters F _in and F _out govern the inclusion and deletion of variables. The candidate variable with the biggest F—ratio is included if this exceeds F _inthe included variable with the smallest F—ratio is deleted if this is less than F _in If F _in ≧F _out; then return to a previous subset size implies improvement in the criterion measure. This result also holds for a generalization, stepwise multivariate analysis, which includes stepwise regression and discriminant analysis as special cases

Eliminations do not occur if forward regression and backward elimination yield the same sequence of subsets. Conversely, there is a more liberal stepping rule which always eliminates if the two sequences differ.     

民族地区经济滞后对和谐社会构建的影响

当前,民族地区经济滞后状况对于构建和谐社会目标的实现产生了极大的阻碍作用：一是动摇 着和谐社会的经济基础;二是成为政治和谐局面的严重隐患;三是削弱着人和自然和谐相处的能力。对此,必 须要给予高度重视。     

Homogeneity tests among groups for microsatellite data

We propose a homogeneity test among groups on a quadratic distance measure. The underlying mutation process in the microsatellite loci is studied using the stepwise mutation model. Asymptotic normality of the test statistic is proved under very mild regularity conditions. Resampling methods, such as jackknife, are used in the application to build confidence intervals for the difference in allelic variation between and within groups. The method is applied in a real data to test whether there are differences in the distribution of the repeated sequence among groups defined by ethnicity and alcoholism index (ALDX1).