Structural effects of network sampling coverage I: Nodes missing at random

Network measures assume a census of a well-bounded population. This level of coverage is rarely achieved in practice, however, and we have only limited information on the robustness of network measures to incomplete coverage. This paper examines the effect of node-level missingness on 4 classes of network measures: centrality, centralization, topology and homophily across a diverse sample of 12 empirical networks. We use a Monte Carlo simulation process to generate data with known levels of missingness and compare the resulting network scores to their known starting values. As with past studies (0035 and 0135), we find that measurement bias generally increases with more missing data. The exact rate and nature of this increase, however, varies systematically across network measures. For example, betweenness and Bonacich centralization are quite sensitive to missing data while closeness and in-degree are robust. Similarly, while the tau statistic and distance are difficult to capture with missing data, transitivity shows little bias even with very high levels of missingness. The results are also clearly dependent on the features of the network. Larger, more centralized networks are generally more robust to missing data, but this is especially true for centrality and centralization measures. More cohesive networks are robust to missing data when measuring topological features but not when measuring centralization. Overall, the results suggest that missing data may have quite large or quite small effects on network measurement, depending on the type of network and the question being posed.     

Intimate Partner Abuse of Older Men: Considerations for the Assessment of Risk

SUMMARY

Intimate partner abuse among older persons, though less common than among the general population, is a significant concern. Drawing from the intimate partner abuse and elder abuse literatures, this paper presents considerations for the assessment of risk for intimate partner abuse perpetrated against older men, with reference to the prevalent gendered view of abuse between intimate partners. Potential victim and perpetrator risk factors specific to this context are discussed and existing risk assessment tools are introduced. Implications and future research directions are discussed with regard to the application of risk assessment technology to this context.     

Individual and systemic/structural bias in child welfare decision making: Implications for children and families of color

The factors contributing to observed racial disproportionality and disparity in the child welfare system have been the subject of national discourse for decades. This qualitative study used focus groups to engage child welfare and collaborating system decision makers, community partners, and families in a subjective interpretive analysis of racial disproportionality and disparity that had been demonstrated by a previous quantitative analysis of Oregon's child welfare system. Thematic analysis yielded eleven themes from the participant focus groups, four of which clustered around individual and structural/systemic bias and are examined in this paper: visibility bias; cultural bias and insensitivity; personal influences on determination of minimally adequate care; and foster and adoptive parent recruitment and licensing practices. Participants offered recommendations to improve outcomes for children and families of color in light of these observations: increase awareness of bias, create checks and balances in decision-making, contract with and hire culturally and racially diverse professionals, and increase funding for training.     

汉蒙语音系统对比及偏误分析

以学习汉语的蒙古学生为研究对象,主要从汉语语音系统的特点出发,以与汉语语音发音相近的蒙语语音为参照,进行汉蒙两种语言的语音对比分析,从而总结出两种语言中由于发音相近而产生的汉语发音的偏误规律。     

An experimental design criterion for minimizing meta-model prediction errors applied to die casting process design

Summary. We propose the expected integrated mean-squared error (EIMSE) experimental design criterion and show how we used it to design experiments to meet the needs of researchers in die casting engineering. This criterion expresses in a direct way the researchers' goal to minimize the expected meta-model prediction errors, taking into account the effects of both random experimental errors and errors deriving from our uncertainty about the true model form. Because we needed to make assumptions about the prior distribution of model coefficients to estimate the EIMSE, we performed a sensitivity analysis to verify that the relative prediction performance of the design generated was largely insensitive to our assumptions. Also, we discuss briefly the general advantages of EIMSE optimal designs, including lower expected bias errors compared with popular response surface designs and substantially lower variance errors than certain Box–Draper all-bias designs.     

自我提升的含义与研究

自我提升是人们追求积极自我意象的驱力,它以优于平均效应、控制错觉、不切实际的乐观、自我服务偏向归因、选择性信息加工、策略性社会比较和交往、自我妨碍等形式实现,可通过一致性比较、自恋和社会赞许倾向评定、作用机制测查、内隐自我提升测量等方法考察,受信息特征、情绪体验、自尊和自我概念、社会情境和文化等因素影响。研究的热点和走向体现在自我动机的整合、测量方法的改进、跨文化研究的引入及发展性研究的兴起等方面。     

Analysis of variance of paired data without repetition of measurement

Summary The objective of this analysis of variance of paired data is to estimate positive random error variances for each ofN=2 measurement methods. The two methods measure the same item only once without measurement repetition. The well-known unbiased Grubbs’ estimators are not suitable for practical purpose because they can become negative. With the help of Chebyshev’s inequality the probability was determined that Grubbs’ estimators become negative. Based on the Grubbs’ estimators new estimators were derived. The new estimators are indeed always positive, but they are biased. It is shown that the biases are small. In case the Grubbs’ estimators are positive a bias correction of the new estimators may be envisaged.

---

Zusammenfassung Das Ziel dieser Varianzanalyse von gepaarten Messungen ist die Sch?tzung zuf?lliger Messfehlervarianzen für jede derN=2 Messmethoden. Die beiden Messmethoden messen das gleiche Merkmal eines Elements nur einmal ohne Messwiederholung. Die bekannten unverzerrten Grubbs-Sch?tzer sind für die praktische Anwendung nicht geeignet, weil sie negativ werden k?nnten. Die Tschebyscheffsche Ungleichung wurde genutzt, um die Wahrscheinlichkeit zu ermitteln, dass Grubbs-Sch?tzer negativ werden. Basierend auf Grubbs-Sch?tzern wurden neue Sch?tzer hergeleitet. Diese neuen Sch?tzer sind zwar immer positiv, aber verzerrt. Es wird gezeigt, dass die Verzerrungen klein sind. Für den Fall, dass die Grubbs-Sch?tzer positiv ausfallen, k?nnte eine Korrektur der Verzerrung in Betracht gezogen werden.

     

Bias in Multinomial Models

This paper investigates bias in parameter estimates and residual diagnostics for parametric multinomial models by considering the effect of deleting a cell. In particular, it describes the average changes in the standardized residuals and maximum likelihood estimates resulting from conditioning on the given cells. These changes suggest how individual cell observations affect biases. Emphasis is placed on the role of individual cell observations in determining bias and on how bias affects standard diagnostic methods. Examples from genetics and log–linear models are considered. Numerical results show that conditioning on an influential cell results in substantial changes in biases.     

《圣经》中的性别歧视

《圣经》是人类文明史上的重要经典之一 ,对西方社会产生了深远的影响 ,它同时开歧视女性之先河。一方面 ,它客观地反映了妇女极其低下的社会地位和极为悲惨的命运 ,表现了当时社会对妇女的歧视 ;另一方面 ,它的文本本身是从男性的视角进行创作的 ,也充满了对女性的歧视。《圣经》对女性的评价和观点 ,成为西方基督教文化歧视女性的源头。