Item Analysis by the Hierarchical Generalized Linear Model

The hierarchical generalized linear model (HGLM) is presented as an explicit, two-level formulation of a multilevel item response model. In this paper, it is shown that the HGLM is equivalent to the Rasch model and that, characteristic of the HGLM, person ability can be expressed in the form of random effects rather than parameters. The two-level item analysis model is presented as a latent regression model with person-characteristic variables. Furthermore, it is shown that the two-level HGLM model can be extended to a three-level latent regression model that permits investigation of the variation of students' performance across groups, such as is found in classrooms and schools, and of the interactive effect of person-and group-characteristic variables.     

Centering,Scale Indeterminacy,and Differential Item Functioning Detection in Hierarchical Generalized Linear and Generalized Linear Mixed Models

In this article, we discuss and illustrate two centering and anchoring options available in differential item functioning (DIF) detection studies based on the hierarchical generalized linear and generalized linear mixed modeling frameworks. We compared and contrasted the assumptions of the two options, and examined the properties of their DIF estimates with a simulation study. For reference purposes, the results were compared to those obtained from using the Mantel-Haenszel procedure as well. Finally, we discuss some implications regarding the choice of model parameterizations for DIF detection using these frameworks.     

The Use of Hierarchical Generalized Linear Model for Item Dimensionality Assessment

To assess item dimensionality, the following two approaches are described and compared: hierarchical generalized linear model (HGLM) and multidimensional item response theory (MIRT) model. Two generating models are used to simulate dichotomous responses to a 17-item test: the unidimensional and compensatory two-dimensional (C2D) models. For C2D data, seven items are modeled to load on the first and second factors, θ₁ and θ₂, with the remaining 10 items modeled unidimensionally emulating a mathematics test with seven items requiring an additional reading ability dimension. For both types of generated data, the multidimensionality of item responses is investigated using HGLM and MIRT. Comparison of HGLM and MIRT's results are possible through a transformation of items' difficulty estimates into probabilities of a correct response for a hypothetical examinee at the mean on θ and θ₂. HGLM and MIRT performed similarly. The benefits of HGLM for item dimensionality analyses are discussed.     

不同刑事审判模式中法官和当事人的地位

在不同的刑事审判模式中,法官和当事人有不同的诉讼地位。在对抗式审判模式中,当事人处于主导地位,法官处于消极公断的地位。在审问式模式中,法官处于主导地位,当事人处于消极地位。不同的法律传统和民族心理是造成法官和当事人在不同的审判模式中处于不同地位的根本原因。这对我国的审判模式的改革具有很大的借鉴作用。我们要立足于我国传统的法律文化,逐步提高当事人在诉讼中的地位,保护当事人的合法权益。     

Item Response Models for Local Dependence Among Multiple Ratings

Ratings given to the same item response may have a stronger correlation than those given to different item responses, especially when raters interact with one another before giving ratings. The rater bundle model was developed to account for such local dependence by forming multiple ratings given to an item response as a bundle and assigning fixed‐effect parameters to describe response patterns in the bundle. Unfortunately, this model becomes difficult to manage when a polytomous item is graded by more than two raters. In this study, by adding random‐effect parameters to the facets model, we propose a class of generalized rater models to account for the local dependence among multiple ratings and intrarater variation in severity. A series of simulations was conducted with the freeware WinBUGS to evaluate parameter recovery of the new models and consequences of ignoring the local dependence or intrarater variation in severity. The results revealed a good parameter recovery when the data‐generating models were fit, and a poor estimation of parameters and test reliability when the local dependence or intrarater variation in severity was ignored. An empirical example is provided.     

广义线性热弹性力学模型的唯一性

In this paper, the uniqueness for the linear theory of a new generalized thermo-elastic model of the continuum with the centre symmetry is shown under less assumptions, whose constitutive equations contain deformation, temperature and its rate as well as its gradient, electric field and its gradient. So the phase variation is pemitted when the deformation proceeds as long as the constitutive equations preserve their original forms.     

Uniqueness for the Linear Theory of Generalized Thermo-Elasticity

1 IntroductionClassical thermodynamics with the Parabolic-typeFourier heat conduction equation predictS that if amaterial conducting heat is subjected tO a thermaldissonance, the effectS of distalance will be feltinstancously at distances infndtely far from its source. Inother words, thermal signals Propagate at infinite speed.This Prediction is ~listic born a physical point ofview (see Ref.[l]). TO overcome such ~asonablenessand avoid the above situations, The new theory is setusually in …     

广义线性模型极大似然估计弱相合性的数值模拟

广义线性模型是经典线性模型的自然推广,它是一类应用广泛的统计模型.选择Probit模型,利用matlab编程,通过数值模拟的方法验证了广义线性模型的极大似然估计的弱相合性.     

广义特征向量的广义线性相关性

研究复数域上亏损矩阵的广义特征向量。根据广义特征子空间链,提出广义特征向量组的广义线性相关与广义线性无关的概念,用以刻画若当链的计算复杂性。     

广义线性模型中拟似然估计的弱相合性及收敛速度

在非自然联系情形下讨论了广义线性模型拟似然方程的解βn在λ—n→∞和其他一些正则性条件下证明了解的弱相合性,并得到其收敛于真值β0的速度为Op(λ—n-1/2),其中λ—n(λ—n)为方阵Sn=iΣ=n1XiX'1的最小(最大)特征值.     

线性结构关系EV模型中参数的可估性分析

从线性回归模型中参数的可估性出发 ,研究了常系数和变系数线性结构关系EV模型中参数可估的条件 .这一条件是很一般的 .     

多层线性模型的原理及应用

本文对多层线性模型 (HierarchicalLinearModels ,HLM)的理论缘起、应用范围以及其应用原理进行了阐述 ,在指出经典统计技术处理多层数据结构上的局限的同时 ,表明了多层线性模型在这方面的优越性。本文最后对多层线性模型的效果及局限性进行了简要分析。     

独立与相依情形下加权广义线性模型选择的重对数律和强一致性

在温和条件下,考虑相依响应情形(ρ-混合或m-相依),针对一般广义线性模型(GLM)任意改变其参数权重构造出加权GLM,给出了参数的最大似然估计(MLE),并推导了加权后模型的重对数律(LIL)。应用独立情形下强极限理论证明了任意修正模型与全模型的对数似然之差的渐近结果。借助惩罚加权对数似然函数技术,基于相依LIL证明了模型选择准则的强一致性,并推导出若惩罚项的阶数介于O(log log n)与O(n)之间时,则该准则选取最简单修正模型几乎是必然的。     

广义组合KdV方程的线性隐式差分格式

目的研究广义组合KdV方程的数值解．方法利用解KdV方程的方法进行讨论．结果给出了广义组合KdV方程的一种线性隐式差分格式．结论这种线性隐式差分格式是无条件稳定的．     

求解广义线性互补问题的一种内点算法

将Yoshise A.提出的求解线性互补问题(LCP)的内点算法进行了推广,由此给出了一种求解广义线性互补问题(GLCP)的内点算法--路径跟踪法.分析了算法对于GLCP的可行性,并在较弱的条件下,证明了该算法具有多项式复杂性.     

特殊情形下线性模型异方差性的LM检验

考虑了特殊情形下具有异方差性的线性模型。首先导出了在模型中当异方差为线性函数时异方差检验的LM检验统计量及其性质,然后举例说明其有效性。     

求解广义水平线性互补问题的一个二次收敛算法

借助Fischer函数将广义水平线性互补问题（HLCP）等价转化为一个方程系统,并利用Levenberg-Marquardt方法,给出一种求解船的新方法,同时在不要求存在非退化解的条件下证明了这种方法的全局和二次收敛。     

半正定系统广义非定常多分裂迭代算法

文章首先给出了广义非定常多分裂算法,并且证明了在一个简洁条件下广义多分裂算法一定半范数收敛,进一步可得到该算法商收敛,该结果是对Cao[2]中结论的推广。     

有限全序语义和广义皮尔斯律

本文将二值逻辑中刻画实质蕴涵的保真性推广至有限全序中,用这推广的"保真性"给出蕴涵在有限全序中的语义条件,从而给出了完整的有限全序语义;建立了刻画有限全序的逻辑系统FO,证明FO的可靠性、完全性和可判定性;提出了广义的皮尔斯律,证明其能区分不同基数的有限全序;给出了FO的扩充系统FOn,证明了FOn刻画了n个元素的全序.     

一元线性结构关系EV模型的假设检验

给出了一元线性结构关系EV模型y=a+bx,Y=y+ε,X=x+u中关于线性关系y=a+bx的假设检验法则.