Optimal Composite Markers for Time‐Dependent Receiver Operating Characteristic Curves with Censored Survival Data

Abstract. To increase the predictive abilities of several plasma biomarkers on the coronary artery disease (CAD)‐related vital statuses over time, our research interest mainly focuses on seeking combinations of these biomarkers with the highest time‐dependent receiver operating characteristic curves. An extended generalized linear model (EGLM) with time‐varying coefficients and an unknown bivariate link function is used to characterize the conditional distribution of time to CAD‐related death. Based on censored survival data, two non‐parametric procedures are proposed to estimate the optimal composite markers, linear predictors in the EGLM model. Estimation methods for the classification accuracies of the optimal composite markers are also proposed. In the article we establish theoretical results of the estimators and examine the corresponding finite‐sample properties through a series of simulations with different sample sizes, censoring rates and censoring mechanisms. Our optimization procedures and estimators are further shown to be useful through an application to a prospective cohort study of patients undergoing angiography.     

Asymptotics for the Hirsch Index

Abstract. The last decade methods for quantifying the research output of individual researchers have become quite popular in academic policy making. The h‐index (or Hirsch index) constitutes an interesting combined bibliometric volume/impact indicator that has attracted a lot of attention recently. It is now a common indicator, available for instance on the Web of Science. In this article, we establish the asymptotic normality of the empirical h‐index. The rate of convergence is non‐standard: , where f is the density of the citation distribution and n is the number of publications of a researcher. In case that the citations follow a Pareto‐type respectively a Weibull‐type distribution as defined in extreme value theory, our general result specializes well to results that are useful for practical purposes such as the construction of confidence intervals and pairwise comparisons for the h‐index. A simulation study for the Pareto‐type case shows that the asymptotic theory works well for moderate sample sizes already.     

Elicitation of multivariate prior distributions: A nonparametric Bayesian approach

In the context of Bayesian statistical analysis, elicitation is the process of formulating a prior density f(·)$f(·)$ about one or more uncertain quantities to represent a person's knowledge and beliefs. Several different methods of eliciting prior distributions for one unknown parameter have been proposed. However, there are relatively few methods for specifying a multivariate prior distribution and most are just applicable to specific classes of problems and/or based on restrictive conditions, such as independence of variables. Besides, many of these procedures require the elicitation of variances and correlations, and sometimes elicitation of hyperparameters which are difficult for experts to specify in practice. Garthwaite et al. (2005) discuss the different methods proposed in the literature and the difficulties of eliciting multivariate prior distributions. We describe a flexible method of eliciting multivariate prior distributions applicable to a wide class of practical problems. Our approach does not assume a parametric form for the unknown prior density f(·)$f(·)$, instead we use nonparametric Bayesian inference, modelling f(·)$f(·)$ by a Gaussian process prior distribution. The expert is then asked to specify certain summaries of his/her distribution, such as the mean, mode, marginal quantiles and a small number of joint probabilities. The analyst receives that information, treating it as a data set D   with which to update his/her prior beliefs to obtain the posterior distribution for f(·)$f(·)$. Theoretical properties of joint and marginal priors are derived and numerical illustrations to demonstrate our approach are given.     

Parameter Estimation for a Bidimensional Partially Observed Ornstein–Uhlenbeck Process with Biological Application

Abstract. We consider a bidimensional Ornstein–Uhlenbeck process to describe the tissue microvascularization in anti‐cancer therapy. Data are discrete, partial and noisy observations of this stochastic differential equation (SDE). Our aim is to estimate the SDE parameters. We use the main advantage of a one‐dimensional observation to obtain an easy way to compute the exact likelihood using the Kalman filter recursion, which allows to implement an easy numerical maximization of the likelihood. Furthermore, we establish the link between the observations and an ARMA process and we deduce the asymptotic properties of the maximum likelihood estimator. We show that this ARMA property can be generalized to a higher dimensional underlying Ornstein–Uhlenbeck diffusion. We compare this estimator with the one obtained by the well‐known expectation maximization algorithm on simulated data. Our estimation methods can be directly applied to other biological contexts such as drug pharmacokinetics or hormone secretions.     

Accountability in the Shadow of Hierarchy: The Horizontal Accountability of Agencies

In the Netherlands, new accountability arrangements are created as remedies for the accountability deficit of agencies. These arrangements are of a ‘horizontal’ nature, as the agencies account for their behaviour towards accountees that are not their hierarchical superiors: clients, stakeholders or peers. This paper provides an inventory and qualitative assessment of horizontal accountability arrangements. It is argued that they have added value because they stimulate learning. However, horizontal accountability is not a substitute for hierarchical accountability. Horizontal accountability arrangements operate ‘in the shadow of hierarchy’: they gain significance through complex interactions with traditional forms of accountability.

基于体积比的多元过程能力指数的Taam算法的改进

随着多元统计过程控制技术的大量应用,多元过程能力指数的定量计算问题受到广泛关注。由于多元过程的复杂性,计算多元过程能力指数一直是一项较为困难的工作,至今尚未形成具有普遍适用性的计算方法。本文对多元过程能力指数的研究文献和当前进展进行了梳理和分析,重点研究了基于体积比的多元过程能力指数的Taam算法,分析了Taam算法存在的主要问题,提出了本文的改进算法,并利用一个经典实例对改进效果进行了对比分析。测算结果表明,Taam算法确实存在内在缺陷,本文的改进算法更为可靠。     

Fisher's Information for Discretely Sampled Lévy Processes

This paper studies the asymptotic behavior of Fisher's information for a Lévy process discretely sampled at an increasing frequency. As a result, we derive the optimal rates of convergence of efficient estimators of the different parameters of the process and show that the rates are often nonstandard and differ across parameters. We also show that it is possible to distinguish the continuous part of the process from its jumps part, and even different types of jumps from one another.     

Speaking of art: Class code or historical residual?

Knowledge and consumption of the fine arts were once considered symbolic of upper class standing. As cultural production has expanded, fine art products in various guises have become accessible to more people across the socioeconomic spectrum. This article looks at how the New York Times covered the American art scene in the 1950s and between 2000 and 2009 to investigate whether reporting has maintained a knowledge-based approach that provides evidence for the continuation of class status as it relates to writing about the arts. We argue that critics and reporters have used fungibility, social hierarchies, and disinterested language during these two time periods to maintain the role of the fine arts as a marker of social distinction.     

创作手记中独特的“这一个＂—读陈忠实《寻找属于自己的句子》

陈忠实的创作手记《寻找属于自己的句子》是展示其长篇小说《白鹿原》艺术生成过程的重要文本。本创作手记从创作发生、构思与物化等基本阶段出发,不仅揭示了《白鹿原》的创作过程、创作理念以及审美追求,还表现了作家丰富真挚的情感世界,并以其独具的情感内蕴与话语特色成为创作手记中独特的“这一个”。     

我国产业结构演变的历史进程与现实问题分析

改革开放以来,我国产业结构演变进程可大致分为三个发展阶段:产业结构演变的加速发展阶段(1978～1991年)、产业结构演变的深化发展阶段(1992～2001年)和产业结构演变的提升发展阶段(2002年至今)。产业结构合理化水平不高和产业结构高级化水平不够仍然是我国产业结构演变进程中面临的主要现实问题,需要全面提升产业结构的合理化和高级化水平,促进产业结构优化升级。