我国海洋区域管理中存在的不协调问题及其对策研究

“协调”是海洋区域管理的核心问题。海洋区域管理要协调各涉海行业间的关系、海洋区域管理部门与涉海行业的关系、管理部门备层级间的关系,以及管理部门与企业、公众的关系等。目前在我国的海洋区域管理中,仍然存在政策法规、管理体制、用海者利益等方面的不协调,困扰着海洋的可持续发展和利用。本文针对目前我国海洋区域管理中存在的不协调问题,分析其存在的原因,并从政策制定、执法保障、制度建设、技术创新等方面寻求解决问题的对策。     

Comparison of several imputation methods for missing baseline data in propensity scores analysis of binary outcome

We performed a simulation study comparing the statistical properties of the estimated log odds ratio from propensity scores analyses of a binary response variable, in which missing baseline data had been imputed using a simple imputation scheme (Treatment Mean Imputation), compared with three ways of performing multiple imputation (MI) and with a Complete Case analysis. MI that included treatment (treated/untreated) and outcome (for our analyses, outcome was adverse event [yes/no]) in the imputer's model had the best statistical properties of the imputation schemes we studied. MI is feasible to use in situations where one has just a few outcomes to analyze. We also found that Treatment Mean Imputation performed quite well and is a reasonable alternative to MI in situations where it is not feasible to use MI. Treatment Mean Imputation performed better than MI methods that did not include both the treatment and outcome in the imputer's model. Copyright © 2009 John Wiley & Sons, Ltd.     

基于方案占优和排序稳健性的多属性决策方法

在多属性决策问题中,不同的属性权重会产生不同的评价结果。由于实际问题的复杂性与不确定性,决策者对于属性权重的确定也存在不确定性。这些不确定既来自现实问题的复杂性和可变性,也来自决策者选择的模糊性与随机性。目前已有的研究主要是将不确定的权重信息转化为相对确定的信息（如转化为区间数等）,硬性地消除了不确定,从而给决策结果带来较大风险。本文从方案排序的视角出发,研究在权重空间下,方案的占优关系和排序的稳健性。首先,定义了占优矩阵用于刻画不确定权重信息下方案两两比较的占优关系;其次,分析了方案的排序区间,即在所有可能存在的权重组合下,方案的最好排序和最差排序。然后,定义了方案的全排序排序概率,并且给出了排序概率的计算方法。进而,我们给出了方法的决策步骤和实施过程。最后,本文将该方法应用到某远洋集团的港口评估当中。     

以社会共生视角开展社会研究

为了探讨社会共生论对社会研究具有的理论及实际操作价值,从社会研究的研究对象、研究内容、概念操作化以及适用范围等方面,阐述了运用社会共生的视角开展社会研究的问题。分析认为,社会共生是一种基本的社会存在,各种社会现象都可以从主体、资源与约束条件三要素入手,用社会共生论进行理论还原;对社会共生现象的研究,本质上就是对共生关系结构的研究。     

基于不同农户群体的土地流转状况分析——来自2014年河北11个地市的农户经验数据

为深入了解目前河北省农户土地流转的现状和影响因素,主要选择了保定、沧州、承德、邯郸、衡水、廊坊、秦皇岛、石家庄、唐山、邢台、张家口等11个地市辖区农户的土地流转情况进行了调研。文章根据此次调查数据,采用经典最小二乘法对不同农户群体土地流入、土地流出面积影响因素进行了分析。结果表明：土地流转市场尚未发生明显的作用;家庭承包土地面积规模对土地流转产生显著性的影响;农户受教育程度对于土地流转程度影响尚不显著。     

Geometric median and its application in the identification of multiple outliers

Geometric mean (GM) is having growing and wider applications in statistical data analysis as a measure of central tendency. It is generally believed that GM is less sensitive to outliers than the arithmetic mean (AM) but we suspect likewise the AM the GM may also suffer a huge set back in the presence of outliers, especially when multiple outliers occur in a data. So far as we know, not much work has been done on the robustness issue of GM. In quest of a simple robust measure of central tendency, we propose the geometric median (GMed) in this paper. We show that the classical GM has only 0% breakdown point while it is 50% for the proposed GMed. Numerical examples also support our claim that the proposed GMed is unaffected in the presence of multiple outliers and can maintain the highest possible 50% breakdown. Later we develop a new method for the identification of multiple outliers based on this proposed GMed. A variety of numerical examples show that the proposed method can successfully identify all potential outliers while the traditional GM fails to do so.     

预测移动支付采纳倾向的关键因素研究——基于神经网络模型的分析

移动支付的采纳对移动商务的发展至关重要。以技术准备理论为基础,对TAM模型进行拓展,结合297份有效样本数据,运用神经网络模型检验预测用户移动支付采纳倾向的关键因素,并与多元回归分析的结果进行比较。研究表明,神经网络模型优于多元回归模型,感知有用性和感知易用性是预测移动支付采纳倾向的最重要因素,之后依次为不适感、乐趣、创新性和不安全感。结合研究结果,对移动支付未来发展提出建议。     

Adaptive graph‐based multiple testing procedures

Multiple testing procedures defined by directed, weighted graphs have recently been proposed as an intuitive visual tool for constructing multiple testing strategies that reflect the often complex contextual relations between hypotheses in clinical trials. Many well‐known sequentially rejective tests, such as (parallel) gatekeeping tests or hierarchical testing procedures are special cases of the graph based tests. We generalize these graph‐based multiple testing procedures to adaptive trial designs with an interim analysis. These designs permit mid‐trial design modifications based on unblinded interim data as well as external information, while providing strong family wise error rate control. To maintain the familywise error rate, it is not required to prespecify the adaption rule in detail. Because the adaptive test does not require knowledge of the multivariate distribution of test statistics, it is applicable in a wide range of scenarios including trials with multiple treatment comparisons, endpoints or subgroups, or combinations thereof. Examples of adaptations are dropping of treatment arms, selection of subpopulations, and sample size reassessment. If, in the interim analysis, it is decided to continue the trial as planned, the adaptive test reduces to the originally planned multiple testing procedure. Only if adaptations are actually implemented, an adjusted test needs to be applied. The procedure is illustrated with a case study and its operating characteristics are investigated by simulations. Copyright © 2014 John Wiley & Sons, Ltd.     

Two New Conditions Supporting the First‐Order Approach to Multisignal Principal–Agent Problems

This paper presents simple new multisignal generalizations of the two classic methods used to justify the first‐order approach to moral hazard principal–agent problems, and compares these two approaches with each other. The paper first discusses limitations of previous generalizations. Then a state‐space formulation is used to obtain a new multisignal generalization of the Jewitt (1988) conditions. Next, using the Mirrlees formulation, new multisignal generalizations of the convexity of the distribution function condition (CDFC) approach of Rogerson (1985) and Sinclair‐Desgagné (1994) are obtained. Vector calculus methods are used to derive easy‐to‐check local conditions for our generalization of the CDFC. Finally, we argue that the Jewitt conditions may generalize more flexibly than the CDFC to the multisignal case. This is because, with many signals, the principal can become very well informed about the agent's action and, even in the one‐signal case, the CDFC must fail when the signal becomes very accurate.     

Testing Models With Multiple Equilibria by Quantile Methods

This paper proposes a method for testing complementarities between explanatory and dependent variables in a large class of economic models. The proposed test is based on the monotone comparative statics (MCS) property of equilibria. Our main result is that MCS produces testable implications on the (small and large) quantiles of the dependent variable, despite the presence of multiple equilibria. The key features of our approach are that (i) we work with a nonparametric structural model of a continuous dependent variable in which the unobservable is allowed to be correlated with the explanatory variable in a reasonably general way; (ii) we do not require the structural function to be known or estimable; (iii) we remain fairly agnostic on how an equilibrium is selected. We illustrate the usefulness of our result for policy evaluation within Berry, Levinsohn, and Pakes's (1999) model.