Model‐based clustering of longitudinal data

A new family of mixture models for the model‐based clustering of longitudinal data is introduced. The covariance structures of eight members of this new family of models are given and the associated maximum likelihood estimates for the parameters are derived via expectation–maximization (EM) algorithms. The Bayesian information criterion is used for model selection and a convergence criterion based on the Aitken acceleration is used to determine the convergence of these EM algorithms. This new family of models is applied to yeast sporulation time course data, where the models give good clustering performance. Further constraints are then imposed on the decomposition to allow a deeper investigation of the correlation structure of the yeast data. These constraints greatly extend this new family of models, with the addition of many parsimonious models. The Canadian Journal of Statistics 38:153–168; 2010 © 2010 Statistical Society of Canada     

Use of non-normality in structural equation modeling: Application to direction of causation

Structural equation modeling (SEM) typically utilizes first- and second-order moment structures. This limits its applicability since many unidentified models and many equivalent models that researchers would like to distinguish are created. In this paper, we relax this restriction and assume non-normal distributions on exogenous variables. We shall provide a solution to the problems of underidentifiability and equivalence of SEM models by making use of non-normality (higher-order moment structures). The non-normal SEM is applied to finding the possible direction of a path in simple regression models. The method of (generalized) least squares is employed to estimate model parameters. A test statistic for examining a fit of a model is proposed. A simulation result and a real data example are reported to study how the non-normal SEM approach works empirically.     

Altruism and information

Experimental literature has accumulated evidence on the association of social identity to a higher or lower level of prosocial behavior. There is also evidence that donations are affected by the mere provision of information about the recipients, whatever its nature or content. In this paper, we present a unified experimental framework (within-subjects) to analyze the impact of different information sets (that concern social class, political orientation or gender) on the level of giving; our experimental design allows us to reveal the effect of three information sets, with respect to the baseline treatment of no information, and separately from the effect of the informational content. A between-subjects replication in M-Turk provides results in the same direction, although the treatment effects are much weaker. These results could be relevant to any design intended to measure the impact on altruism of different dimensions of social identity.     

科技创新能力、区域异质性与中国房价——基于31个省份的实证研究

高房价遏制了科技创新能力，但科技创新能力的提升对房价的推高作用尚未明确。以此为新视角的探究，首先根据经济学理论推演研究假设，而后构建中国31个省份2006年至2017年间的科技创新能力和房价的混合面板数据，采用因子分析法修正科技创新能力指标体系，选用Ward法进行区域异质性分析，进一步结合区域异质性建立多元线性计量模型分析了科技创新能力对房价的影响因素和传导机制。研究发现：从全国范围看，科技创新能力显著推高了房价，主要原因是科技投入中R&D人数的显著增加，而科技创新能力的产出和研发经费投入的正向影响较小；R&D人数的传导机制是通过直接效应和部分中介效应正向影响房价；考虑区域异质性，R&D人数增加在各省份均推高了房价，且科技创新能力非发达区域效应更大；在科技创新能力发达的7个省份中，R&D人员出现"聚集效应"，其他省份出现"溢出效应"。     

Cox regression for current status data with mismeasured covariates

Covariate measurement error problems have been extensively studied in the context of right‐censored data but less so for current status data. Motivated by the zebrafish basal cell carcinoma (BCC) study, where the occurrence time of BCC was only known to lie before or after a sacrifice time and where the covariate (Sonic hedgehog expression) was measured with error, the authors describe a semiparametric maximum likelihood method for analyzing current status data with mismeasured covariates under the proportional hazards model. They show that the estimator of the regression coefficient is asymptotically normal and efficient and that the profile likelihood ratio test is asymptotically Chi‐squared. They also provide an easily implemented algorithm for computing the estimators. They evaluate their method through simulation studies, and illustrate it with a real data example. The Canadian Journal of Statistics 39: 73–88; 2011 © 2011 Statistical Society of Canada     

老年冠心病患者红细胞免疫功能与BNP、CD62P的临床意义

目的探讨老年冠心病（CHD）患者外周血红细胞免疫功能（EIF）与脑钠肽（BNP））、P-选择素（CD62P）的变化及其临床意义。方法采用“郭峰改良法”、干式快速荧光免疫法及流式细胞技术检测88例老年CHD患者外周血红细胞C3b受体花环率（RBC—C3bRR）、红细胞免疫复合花环率（RBC—ICR）、BNP和CD62P,并与32例健康老年人比较。结果CHD组的RBC—C3bRR与对照组无明显差异,RBC—ICR、BNP及CD62P则CHD组明显高于对照组,尤以急性心肌梗死组（AMI）和不稳定型心绞痛组（UAP）为甚（P〈0．01）。结论老年CHD存在严重的EIF低下,免疫机制和炎症因子BNP、CD62P可能是急性冠脉综合症（ACS）发病中的一个重要因素,并可能与斑块的不稳定性有关。     

实验与颠覆：传记中的现代派与后现代

现代派和后现代对传记的真实性原则发起冲击。伍尔芙的《奥兰多传》对传主生平进行变形处理。马尔罗的《反回忆录》打破了叙述的顺序并加上虚构的内容,反映了现代派传记的实验性质。后现代对传记的真实性表示怀疑并颠覆传记的传统标准,奈依关于爱迪生的“反传记”、汤婷婷的《女勇士》、莫里斯的《里根回忆录》和格林布拉特的《尘世威尔》等作品出于不同的价值目标,在传记的外形中加入了更多的虚构和想象。传记要回应这一挑战就应当坚守真实性的原则并承认真实的相对性。     

模糊层次分析法在博士生招生计划分配中的应用研究

采用基于信息合成的模糊层次分析方法,以中国矿业大学博士生招生指标分配问题为背景,将层次分析法中判断矩阵进行优化,运用多个专家的判断矩阵信息进行合成,建立相应的数学模型。该方法能较好地解决博士生招生计划编制中名额分配问题,实现博士研究生招生计划的科学分配和博士生资源的优化配置,但也存在有待完善之处。     

“都”、“也”、“又”主观化用法的异同

副词＂都＂和＂又＂的主观化用法都表示强调语气,＂也＂则表示委婉语气。在极性表达和程度表达方面,＂都＂和＂也＂有一些相同的句法分布,强调表达用＂都＂,委婉表达用＂也＂;在增量表达方面,＂也＂和＂又＂有一些相同的句法分布,委婉表达用＂也＂,强调表达用＂又＂。和强调表达相比,副词的委婉表达要受更多的限制,强调和委婉不是对称的。因此＂也＂和＂都＂、＂也＂和＂又＂的语气表达不是完全平行的。     

Was Quetelet’s Average Man Normal?

Abstract

Quetelet’s data on Scottish chest girths are analyzed with eight normality tests. In contrast to Quetelet’s conclusion that the data are fit well by what is now known as the normal distribution, six of eight normality tests provide strong evidence that the chest circumferences are not normally distributed. Using corrected chest circumferences from Stigler, the χ² test no longer provides strong evidence against normality, but five commonly used normality tests do. The D’Agostino–Pearson K² and Jarque–Bera tests, based only on skewness and kurtosis, find that both Quetelet’s original data and the Stigler-corrected data are consistent with the hypothesis of normality. The major reason causing most normality tests to produce low p-values, indicating that Quetelet’s data are not normally distributed, is that the chest circumferences were reported in whole inches and rounding of large numbers of observations can produce many tied values that strongly affect most normality tests. Users should be cautious using many standard normality tests if data have ties, are rounded, and the ratio of the standard deviation to rounding interval is small.