Estimating the effectiveness of a misdemeanor drug diversion program using propensity score matching and survival analyses

This study analyzes three years of data on misdemeanor drug offenders in Winnebago County, Wisconsin. A portion of these offenders opted into a Misdemeanor Drug Diversion Program (MDDP) offered instead of traditional adjudication. Recidivism in the treatment and comparison groups is estimated using standard binary response techniques augmented with propensity score matching to address selection bias. Results show that the MDDP reduces the probability of re-offense by 16%, after adjusting for possible selection bias. Cox proportional hazard modeling is also used to assess time-to-re-offense differentials between the treatment and comparison groups. The survival analysis indicates that the hazard rate of re-offense is 60% lower per day among those treated with the MDDP program than those who did not complete the program. The average number of days to re-offense among those that do re-offend is 297 days in the treatment group and 203 days in the comparison group.     

Evaluating Probabilistic Forecasts with Bayesian Signal Detection Models

We propose the use of signal detection theory (SDT) to evaluate the performance of both probabilistic forecasting systems and individual forecasters. The main advantage of SDT is that it provides a principled way to distinguish the response from system diagnosticity, which is defined as the ability to distinguish events that occur from those that do not. There are two challenges in applying SDT to probabilistic forecasts. First, the SDT model must handle judged probabilities rather than the conventional binary decisions. Second, the model must be able to operate in the presence of sparse data generated within the context of human forecasting systems. Our approach is to specify a model of how individual forecasts are generated from underlying representations and use Bayesian inference to estimate the underlying latent parameters. Given our estimate of the underlying representations, features of the classic SDT model, such as the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC), follow immediately. We show how our approach allows ROC curves and AUCs to be applied to individuals within a group of forecasters, estimated as a function of time, and extended to measure differences in forecastability across different domains. Among the advantages of this method is that it depends only on the ordinal properties of the probabilistic forecasts. We conclude with a brief discussion of how this approach might facilitate decision making.     

Benchmark Dose Analysis via Nonparametric Regression Modeling

Estimation of benchmark doses (BMDs) in quantitative risk assessment traditionally is based upon parametric dose‐response modeling. It is a well‐known concern, however, that if the chosen parametric model is uncertain and/or misspecified, inaccurate and possibly unsafe low‐dose inferences can result. We describe a nonparametric approach for estimating BMDs with quantal‐response data based on an isotonic regression method, and also study use of corresponding, nonparametric, bootstrap‐based confidence limits for the BMD. We explore the confidence limits’ small‐sample properties via a simulation study, and illustrate the calculations with an example from cancer risk assessment. It is seen that this nonparametric approach can provide a useful alternative for BMD estimation when faced with the problem of parametric model uncertainty.     

我国成品油流通行业市场进入的博弈分析

利用博弈理论分析我国成品油流通市场，发现：适度的、透明的市场进入固定成本对整个市场结构是有利的；要使成品油流通市场更有效率，并保护各方利益，政府应鼓励流通领域竞争，并更大限度地发挥市场配置资源的基础性作用，从而逐渐形成合理有效的市场结构。     

古今偏义复词的对比分析

＂偏义复词＂是一个语言学名词,它具有高度的概括性。古今偏义复词是继承发展的,两者有相同点,但又存在偏指义语素定位、对语境的依赖程度、语素的凝固性、语用等方面的差异,通过对比分析,可提高驾驭语言的能力。     

探讨现代企业财务分析的持续改进的几点建议

分析传统财务分析中存在的主要问题，结合当前的财务分析状况，从企业现金流量情况、资源的效能结构、企业创新能力、企业营销、成本控制等方面提出了一些对策和建议。     

基于趋势面分析的ST类上市公司分布特征研究

上证所与深证所共有1727只股票(含B股)(截止2010年5月7日),其中ST类股票169只.本文运用趋势面分析对ST类股票的分布特征进行了研究.研究结果表明,地理位置与ST类公司的数量之间有显著的相关性,了解其分布特征可以帮助投资者判断某一地理区域投资环境的优劣.     

An International Pooled Analysis for Obtaining a Benchmark Dose for Environmental Lead Exposure in Children

Lead is a recognized neurotoxicant, but estimating effects at the lowest measurable levels is difficult. An international pooled analysis of data from seven cohort studies reported an inverse and supra‐linear relationship between blood lead concentrations and IQ scores in children. The lack of a clear threshold presents a challenge to the identification of an acceptable level of exposure. The benchmark dose (BMD) is defined as the dose that leads to a specific known loss. As an alternative to elusive thresholds, the BMD is being used increasingly by regulatory authorities. Using the pooled data, this article presents BMD results and applies different statistical techniques in the analysis of multistudy data. The calculations showed only a limited variation between studies in the steepness of the dose‐response functions. BMD results were quite robust to modeling assumptions with the best fitting models yielding lower confidence limits (BMDLs) of about 0.1–1.0 μ g/dL for the dose leading to a loss of one IQ point. We conclude that current allowable blood lead concentrations need to be lowered and further prevention efforts are needed to protect children from lead toxicity.     

精神分裂分析：解析资本主义的新视角——读《反俄狄浦斯：资本主义与精神分裂症》

在《反俄狄浦斯：资本主义与精神分裂症》中，法国当代哲学家吉莱斯·德勒兹与利克斯·瓜塔里认为，弗洛伊德的俄狄浦斯情结是人们心中的欲望源泉，又是资本主义统治的基础。因此，为了使人们能够挣脱资本主义，欲望本能需转向为欲望机器。通过精神分裂分析，他们提出了精神分裂症患者才是“去俄狄浦斯化”的革命代理人，这与马克思分析资本主义造就自己掘墓人的思想如出一辙。     

Causality and interdependence analysis in linear econometric models with an application to fertility

This paper is an applied analysis of the causal structure of linear multi-equational econometric models. Its aim is to identify the kind of relationships linking the endogenous variables of the model, distinguishing between causal links and feedback loops. The investigation is first carried out within a deterministic framework and then moves on to show how the results may change inside a more realistic stochastic context. The causal analysis is then specifically applied to a linear simultaneous equation model explaining fertility rates. The analysis is carried out by means of a specific RATS programming code designed to show the specific nature of the relationships within the model.