Explaining the Long Reach of Fathers’ Prenatal Involvement on Later Paternal Engagement

The present study examined the association between unmarried fathers’ prenatal involvement and fathers’ engagement later in the child’s life. The study sample consisted of 1,686 fathers from the Fragile Families and Child Wellbeing Study. Findings using multiple regressions revealed that fathers’ prenatal involvement is significantly and positively associated with levels of fathers’ engagement at Years 1 and 3. This association was partially explained by fathers’ transitions from unemployment to employment and to a greater extent by fathers’ transitions from nonresidential to residential relationships with the child’s mother.     

粗糙群及粗糙商群的部分性质探讨

本文主要讨论了粗糙集理论在代数系统——群上的应用,基于代数系统中的同余关系,提出了粗糙商群的另一定义,进而讨论了粗糙商群的一些性质定理及其证明,同时本文对某些错误定理做了修改并给了证明,而对某些定理的繁琐证明进行了简化。     

Bayesian estimation in the multidimensional three-parameter logistic model

The Gibbs sampler has a great potential to be an efficient and versatile estimation procedure in item response theory. In this article, based on a data augmentation scheme using the Gibbs sampler, we propose a Bayesian procedure to estimate the multidimensional three-parameter logistic model. With the introduction of the two latent variables, the full conditional distributions are tractable, and consequently the Gibbs sampling is easy to implement. Finally, the technique is illustrated by using simulated and real data, respectively.     

Discrepancy measures for item fit analysis in item response theory

Item response theory (IRT) models are commonly used in educational and psychological testing to assess the (latent) ability of examinees and the effectiveness of the test items in measuring this underlying trait. The focus of this paper is on the assessment of item fit for unidimensional IRT models for dichotomous items using a Bayesian method. This paper will illustrate and compare the effectiveness of several discrepancy measures, used within the posterior predictive model check procedure, in detecting misfitted items. The effectiveness of the different discrepancy measures are illustrated in a simulation study using artificially altered simulated data. Using the best discrepancy measure among those studied, this method was applied to real data coming from a mathematics placement exam.     

Choosing colleges: Identifying and modeling choice sets

Although largely ignored in the growing literature about college choice that adopts a random utility modeling framework, there is reason to believe that the estimates are sensitive to the criteria used to define the choice sets. Accordingly, this paper examines the methodological and substantive implications of using merit (class rank) and socioeconomic (high school strata) to define college choice sets. Using Texas as a case study, results show that criteria used to constrain choice sets—and type of high school attend in particular—not only produce quite different post-secondary institutional profiles, but also different estimates of institutional attributes on students’ top choice. These findings have methodological implications for future research about college choice and substantive importance for the prospects that the Texas top 10% law, which guarantees automatic admission to students who graduate in the top decile of their high school class, will equalize access to the state’s competitive public institutions.     

Vague集间相似度量公式的一个分辨力检验法

在应用中相似度量公式的选择是应用成功的关键,提出一种Vague集间相似度量的检验法,可应用于检验一个Vague集间的相似度量公式的分辨能力。     

网络信息过滤的方法和技术研究

网络信息过滤是根据一定的标准和利用一定的工具从动态的网络信息流中选取相关的信息或剔除不相关信息的一系列过程.论述了网络信息过滤的原理,从用户的信息需求与表示,文本的表示技术等方面探讨了网络信息过滤的方法和技术以及存在的问题,提出Vague集之间的相似度量在网络信息过滤中的应用。     

基于语言测试理论的综合英语试题库建设

综合英语是外语专业的基础主干课程之一,课程考核是教学中重要的一环。建设基于语言测试理论的综合英语试题库,可使该课程的考查科学化和标准化。建库时需要考量各种因素,建库过程也要科学严谨,建成后要对题库测试检验,各个环节缺一不可。通过研究,深入分析学生试卷成绩和反馈,进而完善题库,为相关研究提供参考。     

Inferential Theory for Factor Models of Large Dimensions

This paper develops an inferential theory for factor models of large dimensions. The principal components estimator is considered because it is easy to compute and is asymptotically equivalent to the maximum likelihood estimator (if normality is assumed). We derive the rate of convergence and the limiting distributions of the estimated factors, factor loadings, and common components. The theory is developed within the framework of large cross sections (N) and a large time dimension (T), to which classical factor analysis does not apply. We show that the estimated common components are asymptotically normal with a convergence rate equal to the minimum of the square roots of N and T. The estimated factors and their loadings are generally normal, although not always so. The convergence rate of the estimated factors and factor loadings can be faster than that of the estimated common components. These results are obtained under general conditions that allow for correlations and heteroskedasticities in both dimensions. Stronger results are obtained when the idiosyncratic errors are serially uncorrelated and homoskedastic. A necessary and sufficient condition for consistency is derived for large N but fixed T.     

Nonparametric Estimation with Nonlinear Budget Sets

Choice models with nonlinear budget sets provide a precise way of accounting for the nonlinear tax structures present in many applications. In this paper we propose a nonparametric approach to estimation of these models. The basic idea is to think of the choice, in our case hours of labor supply, as being a function of the entire budget set. Then we can do nonparametric regression where the variable in the regression is the budget set. We reduce the dimensionality of this problem by exploiting structure implied by utility maximization with piecewise linear convex budget sets. This structure leads to estimators where the number of segments can differ across observations and does not affect accuracy. We give consistency and asymptotic normality results for these estimators. The usefulness of the estimator is demonstrated in an empirical example, where we find it has a large impact on estimated effects of the Swedish tax reform.