试论我国刑事附带民事诉讼执行

刑事附带民事案件执行比普通民事执行更难,有其自身特殊的原因。解决刑事附带民事执行难问题已不是执行机构单方面的努力所能解决的,而需要公安机关、人民检察院、监狱和刑事审判庭等各个部门的通力合作。解决刑事附带民事执行难的最终机制在于建立国家补偿制度。     

从学生的视角看农村教师的专业发展

教师专业化成长已是当今世界教师教育的主潮流,是各国教育共同关注的焦点问题之一。在调查研究的基础上,从学生的视角对农村教师的专业发展现状进行分析,就促进农村中小学教师专业成长的内容和策略进行理论探讨,是农村教育发展研究的一个课题。     

On the shrinkage of local linear curve estimators

Local linear curve estimators are typically constructed using a compactly supported kernel, which minimizes edge effects and (in the case of the Epanechnikov kernel) optimizes asymptotic performance in a mean square sense. The use of compactly supported kernels can produce numerical problems, however. A common remedy is ridging, which may be viewed as shrinkage of the local linear estimator towards the origin. In this paper we propose a general form of shrinkage, and suggest that, in practice, shrinkage be towards a proper curve estimator. For the latter we propose a local linear estimator based on an infinitely supported kernel. This approach is resistant against selection of too large a shrinkage parameter, which can impair performance when shrinkage is towards the origin. It also removes problems of numerical instability resulting from using a compactly supported kernel, and enjoys very good mean squared error properties.     

Network diversity,contact diversity,and status attainment

We propose that diversity in social relations measured by network diversity and cross-race/cross-gender contacts affords job seekers higher contact status that in turn brings better status attainment outcomes. Controlling for traditional strength of tie measures and other confounders, the empirical study confirms that (1) network diversity in race and gender are significantly associated with actual utilization of cross-race/cross-gender contacts in job search, (2) use of cross-race/cross-gender contacts is significantly related to higher contact status for nonwhite and female job seekers, but (3) contact status (activated social capital) partially provides jobs of higher SEI scores for white job seekers. Similarly, male job seekers obtain better jobs through female contacts, but the same does not apply to female job seekers. These findings show relative return deficits of social capital experienced by racial minorities and females even when they exert extra effort to obtain heterogeneous social relations and contacts.     

An Assessment of Change in Risk Perception and Optimistic Bias for Hurricanes Among Gulf Coast Residents

This study focuses on levels of concern for hurricanes among individuals living along the Gulf Coast during the quiescent two‐year period following the exceptionally destructive 2005 hurricane season. A small study of risk perception and optimistic bias was conducted immediately following Hurricanes Katrina and Rita. Two years later, a follow‐up was done in which respondents were recontacted. This provided an opportunity to examine changes, and potential causal ordering, in risk perception and optimistic bias. The analysis uses 201 panel respondents who were matched across the two mail surveys. Measures included hurricane risk perception, optimistic bias for hurricane evacuation, past hurricane experience, and a small set of demographic variables (age, sex, income, and education). Paired t‐tests were used to compare scores across time. Hurricane risk perception declined and optimistic bias increased. Cross‐lagged correlations were used to test the potential causal ordering between risk perception and optimistic bias, with a weak effect suggesting the former affects the latter. Additional cross‐lagged analysis using structural equation modeling was used to look more closely at the components of optimistic bias (risk to self vs. risk to others). A significant and stronger potentially causal effect from risk perception to optimistic bias was found. Analysis of the experience and demographic variables’ effects on risk perception and optimistic bias, and their change, provided mixed results. The lessening of risk perception and increase in optimistic bias over the period of quiescence suggest that risk communicators and emergency managers should direct attention toward reversing these trends to increase disaster preparedness.     

Semi-doubly optimal concentric circles fitting with presence of heteroscedasticity

Previous studies focus on homogeneous and isotropic assumptions about the noisy data. Many methods have been developed recently for fitting concentric circles to data. In this paper, these statistical assumptions have been relaxed. To the best of our knowledge, only one iterative method has been recently developed. Due to its complexity, no such algorithm is available to compute the reliable maximum likelihood estimator (MLE). Accordingly, we have developed four new methods that outperform the existing methods including the orthogonal distance regression (ODR). We also discuss which of these methods is superior according to the four principles: statistical efficiency, accuracy, robustness, and computational efficiency. Numerical experiments on synthetic and real images have been conducted to validate our findings.     

Discovering hidden statistical issues through individual-level models in ecological studies

ABSTRACT

In ecological studies, individual inference is made based on results from ecological models. Interpretation of the results requires caution since ecological analysis on group level may not hold in the individual level within the groups, leading to ecological fallacy. Using an ecological regression example for analyzing voting behaviors, we highlight that the explicit use of individual-level models is crucial in understanding the results of ecological studies. In particular, we clarify three relevant statistical issues for each individual-level models: assessment of the uncertainty of parameter estimates obtained from a wrong model, the use of shrinkage estimation method for simultaneous estimation of many parameters, and the necessity of sensitivity analysis rather than adhering to one seemingly most compelling assumption.     

Longitudinal relations between behavioral inhibition and social information processing: Moderating role of maternal supportive reactions to children's emotions

Utilizing multiple measures of interpretive biases, the current study examined the roles of toddlers’ behavioral inhibition (BI) and maternal supportive reactions to children's negative emotions in relation to children's interpretive biases across middle to late childhood. Toddlers’ BI was measured during several laboratory tasks (n = 248) at 2 and 3 years of age. Mothers reported on their reactions to children's negative emotional expressions when children were 7 years old (n = 203), and children's interpretations of social cues were assessed at 7 and 10 years of age (n s = 179 and 161, respectively). Toddlers with high levels of BI expressed less positivity toward social engagement with unfamiliar peers during discussion of ambiguous social situations. Further, children with high BI were less likely to attribute the cause of negative social situations to external factors, particularly when mothers were less accepting of children's negative emotional displays. Findings are discussed in terms of cognition related to the interpretation of ambiguous and threat‐related social situations among temperamentally at‐risk children.     

Bootstrap methods for bias correction and confidence interval estimation for nonlinear quantile regression of longitudinal data

This paper examines the use of bootstrapping for bias correction and calculation of confidence intervals (CIs) for a weighted nonlinear quantile regression estimator adjusted to the case of longitudinal data. Different weights and types of CIs are used and compared by computer simulation using a logistic growth function and error terms following an AR(1) model. The results indicate that bias correction reduces the bias of a point estimator but fails for CI calculations. A bootstrap percentile method and a normal approximation method perform well for two weights when used without bias correction. Taking both coverage and lengths of CIs into consideration, a non-bias-corrected percentile method with an unweighted estimator performs best.     

Convergence rates for uniform confidence intervals based on local polynomial regression estimators

We investigate the convergence rates of uniform bias-corrected confidence intervals for a smooth curve using local polynomial regression for both the interior and boundary region. We discuss the cases when the degree of the polynomial is odd and even. The uniform confidence intervals are based on the volume-of-tube formula modified for biased estimators. We empirically show that the proposed uniform confidence intervals attain, at least approximately, nominal coverage. Finally, we investigate the performance of the volume-of-tube based confidence intervals for independent non-Gaussian errors.