试论“统计信息是社会经济信息的主体”

尽管研究信息的文献很多,但迄今为止,对于信息一词尚无公认一致的定义。大致有三种概念。一是广义的概念,认为“信息是人们适应客观世界并使之反作用于客观世界,同客观世界进行交换内容的名称”。二是狭义的概念,把信息定义为“经组织化加以传递的数据”。三是介于广义和狭义之间的概念(姑且把它称之为一般的信息概念),或认为“信息是事物运动状态或变化特征的反映和描述形式”。应该说,三种定义都有一定的道理和长短,但若在问题研究和讨论中,同时以三种概念作为分析的标准,则会产生许多麻烦,甚至相互混淆。为此,我们倾向于选择一般的信息概念作为本文分析的基础。     

On the adequacy of the "sargan distribution"as an approxihation to the normal

The Sargan distribution has been suggested as an alternative to the normal distribution in models Eor which the likelihood function contains the c.d.f. of the errors. However, in such models an incorrect assumption on the error distribution causes the maximum likelihood estimators to be inconsis tent. We calculate this inconsistency, for three simple models. In models with a moderate degree of censoring or truncation, the inconsistency is large e3?0>!gh to he bothersome.     

Restricted mean survival time as a summary measure of time‐to‐event outcome

Many clinical research studies evaluate a time‐to‐event outcome, illustrate survival functions, and conventionally report estimated hazard ratios to express the magnitude of the treatment effect when comparing between groups. However, it may not be straightforward to interpret the hazard ratio clinically and statistically when the proportional hazards assumption is invalid. In some recent papers published in clinical journals, the use of restricted mean survival time (RMST) or τ ‐year mean survival time is discussed as one of the alternative summary measures for the time‐to‐event outcome. The RMST is defined as the expected value of time to event limited to a specific time point corresponding to the area under the survival curve up to the specific time point. This article summarizes the necessary information to conduct statistical analysis using the RMST, including the definition and statistical properties of the RMST, adjusted analysis methods, sample size calculation, information fraction for the RMST difference, and clinical and statistical meaning and interpretation. Additionally, we discuss how to set the specific time point to define the RMST from two main points of view. We also provide developed SAS codes to determine the sample size required to detect an expected RMST difference with appropriate power and reconstruct individual survival data to estimate an RMST reference value from a reported survival curve.     

Rank statistics expressible as integrals under P–P-plots and receiver operating characteristic curves

Given a probability measure on the unit square, the measure of the region under an empirical P – P -plot defines a two-sample rank statistic. Instances include trimmed and censored versions of the Mann–Whitney–Wilcoxon statistic and a class of statistics with applications in the analysis of receiver operating characteristic (ROC) curves. A large sample distribution for such a statistic is obtained, which is valid under sampling from general populations. Explicit results are presented for comparing arbitrary quantile segments of two populations. The results are not restricted to continuous data and incorporate adjustments for tied values in the discrete case. A multivariate version of the large sample distribution extends the class of tractable statistics in ROC analysis and facilitates the use of methods based on partial areas when the data are discrete.     

高新技术企业治理结构对公司绩效的影响——以西安市高新技术企业为例

以西安市高新技术企业为样本,运用因子分析法和多元回归模型实证分析了高新技术企业治理结构对公司绩效的影响。结果显示:董事会结构因子与企业绩效显著正相关,董事会活动因子与企业绩效显著负相关,董事长与总经理两职合一因子与企业绩效显著正相关,股权结构因子和管理层激励因子没有通过显著性检验,这些影响表明高新技术企业治理结构有待改善。     

Using categorical markers as auxiliary variables in log‐rank tests and hazard ratio estimation

Markers, which are prognostic longitudinal variables, can be used to replace some of the information lost due to right censoring. They may also be used to remove or reduce bias due to informative censoring. In this paper, the authors propose novel methods for using markers to increase the efficiency of log‐rank tests and hazard ratio estimation, as well as parametric estimation. They propose a «plug‐in» methodology that consists of writing the test statistic or estimate of interest as a functional of Kaplan–Meier estimators. The latter are then replaced by an efficient estimator of the survival curve that incorporates information from markers. Using simulations, the authors show that the resulting estimators and tests can be up to 30% more efficient than the usual procedures, provided that the marker is highly prognostic and that the frequency of censoring is high.     

Drug development: EU paediatric legislation,the European Medicines Agency and its Paediatric Committee—adolescents’ melanoma as a paradigm

The European Medicines Agency (EMA) website lists all diseases that officially exist in adults only. The class waiver for juvenile melanoma was revoked in 2008 referring to US SEER statistics. This statistical justification is misleading. Melanoma in adolescents is much rarer than claimed by EMA/Paediatric Committee; < 1 ∕ 4 of adolescents with melanoma need systemic treatment; separate efficacy studies are neither medically justified nor feasible. The scarce adolescent patients should be allowed to participate in adult trials. To force companies to investigate them separately turns them into paediatric hostages, to adapt the term therapeutic orphans coined in 1968 by Shirkey. There are now five melanoma Paediatric Investigation Plans (PIPs). Probably none of the PIP‐triggered clinical studies will ever be completed; we propose to call them ghost studies. An oncology research network considering a reasonable trial in melanoma, including adolescents, will compete for recruitment with the PIP‐triggered trials designed by regulatory tunnel vision and sponsored by companies under EMA‐imposed pressure. EMA/Paediatric Committee's territorial enthusiasm (“our patients”) damages oncology research. Copyright © 2014 John Wiley & Sons, Ltd.     

L p –Estimators as Estimates of a Parameter of Location for a Sharp–pointed Symmetric Density

We study the asymptotics of L _p estimators, p > 0, over a sample having a symmetric density with a sharp–point at the centre of symmetry of the distribution. The rates of convergence of the L _p estimators in this situation depend on p and on the shape of the density. To obtain some of the limit distributions, we present new results in the asymptotics of M–estimators. We extend the delta method to the case when the Euclidean norm of the conveniently normalized M–estimators converge to a power of the Euclidean norm of a (possibly Gaussian) stable distribution.     

Expected loss functions as additional measures to assess performance of multiple testing procedures for combination drug dose finding

There are several measures that are commonly used to assess performance of a multiple testing procedure (MTP). These measures include power, overall error rate (family‐wise error rate), and lack of power. In settings where the MTP is used to estimate a parameter, for example, the minimum effective dose, bias is of interest. In some studies, the parameter has a set‐like structure, and thus, bias is not well defined. Nevertheless, the accuracy of estimation is one of the essential features of an MTP in such a context. In this paper, we propose several measures based on the expected values of loss functions that resemble bias. These measures are constructed to be useful in combination drug dose response studies when the target is to identify all minimum efficacious drug combinations. One of the proposed measures allows for assigning different penalties for incorrectly overestimating and underestimating a true minimum efficacious combination. Several simple examples are considered to illustrate the proposed loss functions. Then, the expected values of these loss functions are used in a simulation study to identify the best procedure among several methods used to select the minimum efficacious combinations, where the measures take into account the investigator's preferences about possibly overestimating and/or underestimating a true minimum efficacious combination. The ideas presented in this paper can be generalized to construct measures that resemble bias in other settings. These measures can serve as an essential tool to assess performance of several methods for identifying set‐like parameters in terms of accuracy of estimation. Copyright © 2012 John Wiley & Sons, Ltd.     

Bootstrapping: as easy as 1-2-3

The bootstrap is a powerful non-parametric statistical technique for making probability-based inferences about a population parameter. Through a Monte-Carlo resampling simulation, bootstrapping empirically generates a statistic's entire distribution. From this simulated distribution, inferences can be made about a population parameter. Assumptions about normality are not required. In general, despite its power, bootstrapping has been used relatively infrequently in social science research, and this is particularly true for business research. This under-utilization is likely due to a combination of a general lack of understanding of the bootstrap technique and the difficulty with which it has traditionally been implemented. Researchers in the various fields of business should be familiar with this powerful statistical technique. The purpose of this paper is to explain how this technique works using Lotus 1-2-3, a software package with which business people are very familiar.     

Calibration as estimation

Calibration in macroeconomics involves choosing fre parameters by matching certain moments of simulted models with those of data. We formally examine this method by treating the process of calibration as an econometric estimator. A numerical version of the Mehra-Prescott (1985) economy is the setting for an evaluation of calibration estimators via Monte Carlo methods. While these estimators sometimes have reasonable finite-sample properties they are not robust to mistakes in setting non-free parameters. In contrast, generalized method-of-moments (GMM) estimators have satisfactory finite-sample characteristics, quick convergence, and informational requirements less stringent than those of calibration estimators. In dynamic equilibrium models in which GMM is infeasible we offer some suggestions for improving estimates based on calibration methodology.     

When a Constant Classifier is as Good as Any Linear Classifier

A classifier is constant if it classifies all examples into just one class. Call a training data set “(linearly) indiscriminate” if a constant classifier minimizes, among all linear classifiers, the misclassification rate on the training data set. General sufficient conditions are presented for the probability of getting an indiscriminate data set to be positive. Similarly, general sufficient conditions are also presented for the probability of getting an indiscriminate data set to be 0.

A small simulation study examines how our results are reflected in the behavior of logistic regression.     

2<Superscript><Emphasis Type="Italic">m</Emphasis></Superscript>4<Superscript>1</Superscript> designs with minimum aberration or weak minimum aberration

For measuring the goodness of 2 ^m 4¹ designs, Wu and Zhang (1993) proposed the minimum aberration (MA) criterion. MA 2 ^m 4¹ designs have been constructed using the idea of complementary designs when the number of two-level factors, m, exceeds n/2, where n is the total number of runs. In this paper, the structures of MA 2 ^m 4¹ designs are obtained when m>5n/16. Based on these structures, some methods are developed for constructing MA 2 ^m 4¹ designs for 5n/16<m<n/2 as well as for n/2≤m<n. When m≤5n/16, there is no general method for constructing MA 2 ^m 4¹ designs. In this case, we obtain lower bounds for A ₃₀ and A ₃₁, where A ₃₀ and A ₃₁ are the numbers of type 0 and type 1 words with length three respectively. And a method for constructing weak minimum aberration (WMA) 2 ^m 4¹ designs (A ₃₀ and A ₃₁ achieving the lower bounds) is demonstrated. Some MA or WMA 2 ^m 4¹ designs with 32 or 64 runs are tabulated for practical use, which supplement the tables in Wu and Zhang (1993), Zhang and Shao (2001) and Mukerjee and Wu (2001).     

Cumulants as iterated integrals

A formula expressing cumulants in terms of iterated integrals of the distribution function is derived. It generalizes results of Jones and Balakrishnan who computed expressions for cumulants up to order 4.