Development of Science Anxiety Scale for Primary School Students

The principal aim of the study is to develop a new scale Science Anxiety Scale and to examine its the psychometric properties and construct validity of the Science Anxiety Scale in a sample of 797 primary school students. Exploratory factor analysis was applied and found to have a two-dimensional structure. Confirmatory factor analyses provide evidence for a solid two-dimension structure reflecting the theorized construct: personal and environmental. Also, for convergent validity, item reliability, construct reliability and average variance values were calculated and it was found that item reliability and construct reliability values generally provided the required criteria. The average variance extracted value had a value below the criteria value for both sub-dimensions. Discriminant validity was above the criteria value in all dimensions. The reliability of the Science Anxiety Scale scales appeared to be satisfactory, with good internal consistency. The Science Anxiety Scale was found to be reliable and valid for the Turkish primary student context with a few exceptions.     

外商直接投资与技术进步的相关性研究——基于对1981～2005年长三角与珠三角地区的分析

本文首先将全要素生产率分解为技术效率和技术进步两部分,并采用数据包络分析方法计算出1981年~2005年长三角和珠三角地区的技术效率与技术进步。进而根据格兰杰因果检验与误差修正模型分析这两个地区外商直接投资与技术进步之间的关系,发现两者呈显著负相关。但是,外商直接投资与技术效率之间具有显著的正相关关系。这一结果提示我们,虽然改革开放以来长三角和珠三角地区吸引了大量外商直接投资,但是实际上蜂拥而至的大量跨国公司和外商投资对当地的技术进步并没有显著的贡献,它们主要改善的是当地的技术效率。     

Multilevel Mixed Linear Models for Survival Data

For the analysis of correlated survival data mixed linear models are useful alternatives to frailty models. By their use the survival times can be directly modelled, so that the interpretation of the fixed and random effects is straightforward. However, because of intractable integration involved with the use of marginal likelihood the class of models in use has been severely restricted. Such a difficulty can be avoided by using hierarchical-likelihood, which provides a statistically efficient and fast fitting algorithm for multilevel models. The proposed method is illustrated using the chronic granulomatous disease data. A simulation study is carried out to evaluate the performance.     

Object Interaction and Walking: Integration of Old and New Skills in Infant Development

Manual skills such as reaching, grasping, and exploring objects appear months earlier in infancy than locomotor skills such as walking. To what extent do infants incorporate an old skill (manual actions on objects) into the development of a new skill (walking)? We video recorded 64 sessions of infants during free play in a laboratory playroom. Infants’ age (12.7–19.5 months), walking experience (0.5–10.3 months), and walking proficiency (speed, step length, etc.) varied widely. We found that the earlier developing skills of holding and exploring objects were immediately incorporated into the later developing skill of walking. Although holding incurred a reliable cost to infants’ gait patterns, holding and exploring objects in hand were relatively common activities and did not change with development. Moreover, holding objects was equally common in standing and walking. However, infants did not interact with objects indiscriminately: Object exploration was more frequent while standing than walking, and infants selectively chose lighter objects to carry and explore. Findings suggest that the earlier appearance of some skills may serve to motivate and enrich later appearing skills.     

Analysis of interval censored competing risk data with missing causes of failure using pseudo values approach

Competing risks often occur when subjects may fail from one of several mutually exclusive causes. For example, when a patient suffering a cancer may die from other cause, we are interested in the effect of a certain covariate on the probability of dying of cancer at a certain time. Several approaches have been suggested to analyse competing risk data in the presence of complete information of failure cause. In this paper, our interest is to consider the occurrence of missing causes as well as interval censored failure time. There exist no method to discuss this problem. We applied a Klein–Andersen's pseudo-value approach [Klein, JP Andersen PK. Regression modeling of competing risks data based on pseudovalues of the cumulative incidence function. Biometrics. 2005;61:223–229] based on the estimated cumulative incidence function and a regression coefficient is estimated through a multiple imputation. We evaluate the suggested method by comparing with a complete case analysis in several simulation settings.     

Estimation of Parameters of a Clipped MA(1) Process

Let {X _t , t ∈ ?} be a sequence of iid random variables with an absolutely continuous distribution. Let a > 0 and c ∈ ? be some constants. We consider a sequence of 0-1 valued variables {ξ _t , t ∈ ?} obtained by clipping an MA(1) process X _t  ? aX _t?1 at the level c, i.e., ξ _t  = I[X _t  ? aX _t?1 < c] for all t ∈ ?. We deal with the estimation problem in this model. Properties of the estimators of the parameters a and c, the success probability p, and the 1-lag autocorrelation r ₁ are investigated. A numerical study is provided as an illustration of the theoretical results.     

GMM inference in spatial autoregressive models

In this study, we investigate the finite sample properties of the optimal generalized method of moments estimator (OGMME) for a spatial econometric model with a first-order spatial autoregressive process in the dependent variable and the disturbance term (for short SARAR(1, 1)). We show that the estimated asymptotic standard errors for spatial autoregressive parameters can be substantially smaller than their empirical counterparts. Hence, we extend the finite sample variance correction methodology of Windmeijer (2005 Windmeijer, F. (2005). A finite sample correction for the variance of linear efficient two-step GMM estimators. Journal of Econometrics 126(1):25–51.[Crossref], [Web of Science ®] , [Google Scholar]) to the OGMME for the SARAR(1, 1) model. Results from simulation studies indicate that the correction method improves the variance estimates in small samples and leads to more accurate inference for the spatial autoregressive parameters. For the same model, we compare the finite sample properties of various test statistics for linear restrictions on autoregressive parameters. These tests include the standard asymptotic Wald test based on various GMMEs, a bootstrapped version of the Wald test, two versions of the C(α) test, the standard Lagrange multiplier (LM) test, the minimum chi-square test (MC), and two versions of the generalized method of moments (GMM) criterion test. Finally, we study the finite sample properties of effects estimators that show how changes in explanatory variables impact the dependent variable.     

Two Novel Evolutionary Formulations of the Graph Coloring Problem

We introduce two novel evolutionary formulations of the problem of coloring the nodes of a graph. The first formulation is based on the relationship that exists between a graph's chromatic number and its acyclic orientations. It views such orientations as individuals and evolves them with the aid of evolutionary operators that are very heavily based on the structure of the graph and its acyclic orientations. The second formulation, unlike the first one, does not tackle one graph at a time, but rather aims at evolving a program to color all graphs belonging to a class whose members all have the same number of nodes and other common attributes. The heuristics that result from these formulations have been tested on some of the Second DIMACS Implementation Challenge benchmark graphs, and have been found to be competitive when compared to the several other heuristics that have also been tested on those graphs.     

游离与契合：网络时代的信息策略初论

本文基于对人类信息行为的哲学分析和经验观察,阐释了网络时代的信息管制策略的思想依据和复杂后果。论文通过研究信息的人本意义和时间维度问题,探讨了“信息质”的概念和传媒的“信号博弈”,以此作为思辨工具,作者详尽分析了不同的“离合”(传播信息的游离与契合之间的比值)配置对于不同时期的不同传播对象的传播效用。最后,文章把媒介及把关人如何管制信息传播的问题,归结为不同社会阶层所持有的信息效用理念的冲突。