Young Fatherhood and Subsequent Disadvantage in the United Kingdom

Although there has been increasing attention to the importance of fathers and their relationships with their children, few studies have examined young parenthood and its consequences for fathers’ life chances. In recent years, this has begun to change, and research is examining, to a far greater extent, the experiences of young fathers. Using data from a cohort of British men born in 1970, this paper uses a propensity score–matching technique to compare the well‐being of 344 men who reported becoming fathers before the age of 22 with men from similar backgrounds who did not. The findings suggest that selection into young fatherhood is substantial but, for some outcomes, significant differences remain.     

基于数据仓库的大学生诚信评估系统设计

结合金融系统广泛采用的FICO个人信用评估思想,提出了大学生诚信评价的加减分模型,构建了大学生诚信评估系统(CESS)指标体系及其数据仓库,实现了诚信数据校内整合与共享,并分别以ASP和VB.NET为工具开发了Web及C/S两种风格的CESS系统,介绍了系统结构与功能设计,讨论了包括直接利用Analysis Services多维分析工具实现的丰富的信用查询与统计方式,通过实际数据测试表明,CESS系统能够较好地满足高校需要.     

MORE INFORMATIVE TESTING FOR BIVARIATE SYMMETRY

In testing for bivariate symmetry against arbitrary alternatives the well‐known test developed by Bowker in 1948 is shown to be a score test, and to have useful components. These components are asymptotically independent and asymptotically have the standard normal distribution. Moreover they assess particular pairs of cells for symmetry. These components can also be used in a data analytic manner to complement a test for bivariate symmetry against ordered alternatives.     

Marital disruption and economic well-being: a comparative analysis

Summary.  Though there is a considerable literature concerned with the economic consequences of marital breakdown, there is still substantial disagreement in terms of its magnitude. One of the major problems underlying this debate is how economic well-being is defined. We implement several measures of well-being of monetary and multidimensional nature by using data from the European Community Household Panel. Another issue in this literature concerns selection bias of divorcing couples. We tackle this issue by using a propensity score matching technique combined with a difference-in-differences estimator. Results confirm the importance of the definition of well-being. We find a strong gender bias when using monetary measures but a considerably lower bias, and for some countries non-existent, when using non-monetary indices.     

Third-grade retention and reading achievement in Texas: A nine year panel study

The academic performance of over 38,000 Texas students who failed the state’s 1994 reading test was examined through their sophomore year in high school. Propensity score matching resulted in strata with retained and promoted students of comparable observed characteristics. Reading scores were analyzed using a two-level hierarchical linear model. Same grade comparisons show that third graders failing the state-mandated reading test who repeated the grade consistently outperformed in later grades the socially promoted children who also failed the third grade test. Additional analyses indicate that alternative explanations for the findings such as omitted variables, regression to the mean, differential panel attrition and cohort effects are not supported. The results are consistent with findings from other recent studies which suggest that grade retention in third grade may help increase student achievement.     

A variance shift model for detection of outliers in the linear mixed measurement error models

ABSTRACT

In this paper, we extend a variance shift model, previously considered in the linear mixed models, to the linear mixed measurement error models using the corrected likelihood of Nakamura (1990 Nakamura, T. (1990). Corrected score function for errors in variables models: methodology and application to generalized linear models. Biometrika 77:127–137.[Crossref], [Web of Science ®] , [Google Scholar]). This model assumes that a single outlier arises from an observation with inflated variance. We derive the score test and the analogue of the likelihood ratio test, to assess whether the ith observation has inflated variance. A parametric bootstrap procedure is implemented to obtain empirical distributions of the test statistics. Finally, results of a simulation study and an example of real data are presented to illustrate the performance of proposed tests.     

An improved comorbidity summary score for measuring disease burden and predicting mortality with applications to two national cohorts

Abstract

Research involving administrative healthcare data to study patient outcomes requires the investigator to account for the patient’s disease burden in order to reduce the potential for biased results. Here we develop a comorbidity summary score based on variable importance measures derived from several statistical and machine learning methods and show it has superior predictive performance to the Elixhauser and Charlson indices when used to predict 1-year, 5-year, and 10-year mortality. We used two large Veterans Administration cohorts to develop and validate the summary score and compared predictive performance using the area under ROC curve (AUC) and the Brier score.     

Analysing exponential family based messy data

Recently exponential family based random effects models have received considerable attention. These models usually arise from an unobservable random process added to the independent exponential family models. An unobservable correlated process, however, would cause correlations among the exponential family based data. This paper, first, develops an asymptotically optimal test for testing the appropriateness of a fixed effects model for the exponential family based independent data versus a random effects model for the exponential family based independent or correlated data. The paper, then, provides a general framework on regression analysis for the exponential family based data generated under the random effects models.     

Multivariate Control Charts Based on Hybrid Novelty Scores

We propose a new nonparametric multivariate control chart that integrates a novelty score. The proposed control chart uses as its monitoring statistic a hybrid novelty score, calculated based on the distance to local observations as well as on the distance to the convex hull constructed by its neighbors. The control limits of the proposed control chart were established based on a bootstrap method. A rigorous simulation study was conducted to examine the properties of the proposed control chart under various scenarios and compare it with existing multivariate control charts in terms of average run length (ARL) performance. The simulation results showed that the proposed control chart outperformed both the parametric and nonparametric Hotelling's T ² control charts, especially in nonnormal situations. Moreover, experimental results with real semiconductor data demonstrated the applicability and effectiveness of the proposed control chart. To increase the capability to detect small mean shift, we propose an exponentially weighted hybrid novelty score control chart. Simulation results indicated that exponentially weighted hybrid score charts outperformed the hybrid novelty score based control charts.     

Optimal testing in a three way anova model

We consider likelihood ratio, score and Wald tests for a three-way random effects ANOVA model. Competitor tests are compared using criteria such as small sample power, asymptotic relative efficiency, and convenient null distribution. The final choice is between a new test and two tests long used in practice.