Predictors for resolution of antisocial behavior among foster care youth receiving community-based services

Youth in the foster care system are more likely to be diagnosed with mental illness than those in the general population. Within this system, youth with antisocial behavior (e.g., aggressive, oppositional) are overrepresented. The challenges youth with antisocial behavior present to foster care systems make understanding the factors that predict remission in this population important for improving placement stability. Using Optimal Data Analysis (ODA), this study examines potential moderating effects of various individual, social, and strength variables on clinically significant decreases antisocial behavior in a sample of foster care youth over time. Results revealed positive improvements in youths' wellbeing to be the optimal predictor of resolution, followed by positive changes in family functioning and positive changes in adjustment to trauma (i.e., symptoms of PTSD). These results indicate that clinically significant decreases over time in antisocial behavior were associated with concurrent improvement in individual and environmental variables. Implications for service providers working with this population are discussed.     

Evaluating systems change in a juvenile justice reform initiative

Evaluating comprehensive, interagency initiatives to reform human services systems presents substantial challenges to traditional research models. Outcomes are observed at the system level rather than the individual level, and the validity of study results may be challenged on a variety of dimensions, particularly small sample sizes and measurement error. We report the results of a cross-site evaluation of the first phase of Reclaiming Futures, a five-year effort to improve services and interventions for justice-involved youth in 10 communities across the United States. We present the evaluation findings and discuss implications for similar research endeavors. The methods used in this study may be useful for other system-level evaluation efforts. A social network analysis analyzes changes in the size, density, and cohesiveness of stakeholder networks. Bivariate models test for associations between Reclaiming Futures implementation and key stakeholder perceptions of effective system change. Multivariate models are used to explore selection effects on item response. In general, we find positive correlations between successful implementation of Reclaiming Futures and indicators of effective and efficient system change.     

Sibling sexual abuse: an empirical analysis of offender, victim, and event characteristics in National Incident-Based Reporting System (NIBRS) data, 2000-2007

Sibling sexual abuse is identified as the most common form of familial sexual abuse. Extant literature is plagued by definitional inconsistencies, data limitations, and inadequate research methodology. Trivialized as "normal" sexual exploration, sibling sexual abuse has been linked to psychosocial/psychosexual dysfunction. Research has relied on retrospective, convenience, and/or homogenous samples. This work drew on eight years of National Incident-Based Reporting System data (2000-2007) to provide aggregate level baseline information. This work extended prior research exploring victim-, offender-, and incident-based characteristics. Results highlight the need for expanded definitional criteria relating to both age and gender to better inform risk assessment and prevention. Findings both corroborate and contrast prior work and suggest victim- and offender-based gender differences.     

The Association Between Consumer Debt and the Likelihood of Divorce

As part of the Center for Financial Security’s 2010 symposium, this study examined the association between consumer debt and divorce. Longitudinal data from the National Survey of Families and Households (N = 4,574 couples) indicated that consumer debt was positively associated with divorce. Financial conflict completely mediated this association for both husbands and wives and marital satisfaction also completely mediated the association for wives. These findings suggest that when families take financial steps to secure their financial stability they may also be taking steps to secure their relationship stability.     

The Shift towards Family Reunification in Romanian Child Welfare Policy: An Analysis of Changing Forms of Governmental Intervention in Romania

This article examines the transition in Romanian child welfare policy from a paternalistic attitude of taking responsibility for ‘abandoned’ children to a capitalist orientation of reinstating responsibility for ‘abandoned’ children to the private sphere. While this shift in child policy is often seen to reflect a withdrawal of the public sphere from the private world of childcare, this study argues, alternatively, that this shift demonstrates a change in the form of governmental intervention. This article is based on ethnographic research that examines the reflections of Romanian child welfare professionals upon their changing roles.     

杂合灰色聚类与变精度粗糙模糊集的概率决策方法及应用

在基于粗糙集理论或扩展粗糙集理论的不确定性决策中,仅由数据集无法获得决策表,同时由于决策属性呈现模糊性,以致于难以获取概率决策规则。针对这一类决策问题,基于灰色定权聚类与优势粗糙集变精度方法,本文构建了一种的杂合决策方法。该方法首先利用中心点三角白化权函数的灰色定权聚类方法将包含不同量纲指标的知识表示系统生成多属性决策表,而后运用变精度粗糙模糊集进行决策分析,生成概率决策规则,最后以区域关键技术的选择为例,表明该模型的可行性与实用性。     

Sample‐size calculations for multi‐group comparison in population pharmacokinetic experiments

This paper describes an approach for calculating sample size for population pharmacokinetic experiments that involve hypothesis testing based on multi‐group comparison detecting the difference in parameters between groups under mixed‐effects modelling. This approach extends what has been described for generalized linear models and nonlinear population pharmacokinetic models that involve only binary covariates to more complex nonlinear population pharmacokinetic models. The structural nonlinear model is linearized around the random effects to obtain the marginal model and the hypothesis testing involving model parameters is based on Wald's test. This approach provides an efficient and fast method for calculating sample size for hypothesis testing in population pharmacokinetic models. The approach can also handle different design problems such as unequal allocation of subjects to groups and unbalanced sampling times between and within groups. The results obtained following application to a one compartment intravenous bolus dose model that involved three different hypotheses under different scenarios showed good agreement between the power obtained from NONMEM simulations and nominal power. Copyright © 2009 John Wiley & Sons, Ltd.     

Markov Chains and De-initializing Processes

We define a notion of de-initializing Markov chains. We prove that to analyse convergence of Markov chains to stationarity, it suffices to analyse convergence of a de-initializing chain. Applications are given to Markov chain Monte Carlo algorithms and to convergence diagnostics.