Costs of promoting cancer screening: Evidence from CDC’s Colorectal Cancer Control Program (CRCCP)

The Colorectal Cancer Control Program (CRCCP) provided funding to 29 grantees to increase colorectal cancer screening. We describe the screening promotion costs of CRCCP grantees to evaluate the extent to which the program model resulted in the use of funding to support interventions recommended by the Guide to Community Preventive Services (Community Guide). We analyzed expenditures for screening promotion for the first three years of the CRCCP to assess cost per promotion strategy, and estimated the cost per person screened at the state level based on various projected increases in screening rates. All grantees engaged in small media activities and more than 90% used either client reminders, provider assessment and feedback, or patient navigation. Based on all expenditures, projected cost per eligible person screened for a 1%, 5%, and 10% increase in state-level screening proportions are $172, $34, and $17, respectively. CRCCP grantees expended the majority of their funding on Community Guide recommended screening promotion strategies but about a third was spent on other interventions. Based on this finding, future CRC programs should be provided with targeted education and information on evidence-based strategies, rather than broad based recommendations, to ensure that program funds are expended mainly on evidence-based interventions.     

Asymptotic approximations to the distribution of Kendall's sample τ

This paper provides a saddlepoint approximation to the distribution of the sample version of Kendall's τ, which is a measure of association between two samples. The saddlepoint approximation is compared with the Edgeworth and the normal approximations, and with the bootstrap resampling distribution. A numerical study shows that with small sample sizes the saddlepoint approximation outperforms both the normal and the Edgeworth approximations. This paper gives also an analytical comparison between approximated and exact cumulants of the sample Kendall's τ when the two samples are independent.     

Nonparametric Bayesian inference for multivariate density functions using Feller priors

Multivariate density estimation plays an important role in investigating the mechanism of high-dimensional data. This article describes a nonparametric Bayesian approach to the estimation of multivariate densities. A general procedure is proposed for constructing Feller priors for multivariate densities and their theoretical properties as nonparametric priors are established. A blocked Gibbs sampling algorithm is devised to sample from the posterior of the multivariate density. A simulation study is conducted to evaluate the performance of the procedure.     

An integrated model based on statistical process control and maintenance for two-stage dependent processes

The close relationship between quality and maintenance of manufacturing systems has contributed to the development of integrated models which use the concept of statistical process control (SPC) and maintenance. This article demonstrates the integration of the Shewhart individual-residual (Z_X ? Z_e) joint control chart and maintenance for two-stage dependent processes by jointly optimizing their policies to minimize the expected total costs associated with quality, maintenance and inspection. To evaluate the effectiveness of the proposed model, two stand-alone models—a maintenance model and an SPC model—are proposed. Then a numerical example is given to illustrate the application of the proposed integrated model. The results show that the integrated model outperforms the two stand-alone models with regard to the expected cost per unit time. Finally, a sensitivity analysis is conducted to develop insights into time parameters and cost parameters that influence the integration efforts.     

城市高密度人口分布下的社区建设——以广州荔湾区为例

以广州荔湾区“六普”资料为根据，就人口高密度分布与社区建设的关系进行梳理与探讨。荔湾区“六普”数据显示，城区人口密度过高，成为影响社区生活的主要因素，给居民生命安全、公共生活质量与日常生活便利性带来负面效应。科学化与人性化人口密度干预是治理高密度人口问题的理性策略，如“跳出”社区视野，在城市“一盘棋”中均衡人口布局，在社区建设中，通过社区更新改造，增强人口承载能力，通过建构便利舒适人居环境，提升社区生活质量。     

Simulation techniques for generalized Gaussian densities

This contribution deals with the Monte Carlo simulation of generalized Gaussian random variables. Such a parametric family of distributions has been proposed in many applications in science to describe physical phenomena and in engineering, and it seems to be also useful in modelling economic and financial data. For values of the shape parameter α within a certain range, the distribution presents heavy tails. In particular, the cases α=1/3 and α=1/2 are considered. For such values of the shape parameter, different simulation methods are assessed.     

A Hellinger distance approach to MCMC diagnostics

Bayesian analysis often requires the researcher to employ Markov Chain Monte Carlo (MCMC) techniques to draw samples from a posterior distribution which in turn is used to make inferences. Currently, several approaches to determine convergence of the chain as well as sensitivities of the resulting inferences have been developed. This work develops a Hellinger distance approach to MCMC diagnostics. An approximation to the Hellinger distance between two distributions f and g based on sampling is introduced. This approximation is studied via simulation to determine the accuracy. A criterion for using this Hellinger distance for determining chain convergence is proposed as well as a criterion for sensitivity studies. These criteria are illustrated using a dataset concerning the Anguilla australis, an eel native to New Zealand.     

Smooth tail-index estimation

The two parametric distribution functions appearing in the extreme-value theory – the generalized extreme-value distribution and the generalized Pareto distribution – have log-concave densities if the extreme-value index γ∈[?1, 0]. Replacing the order statistics in tail-index estimators by their corresponding quantiles from the distribution function that is based on the estimated log-concave density ? f _n leads to novel smooth quantile and tail-index estimators. These new estimators aim at estimating the tail index especially in small samples. Acting as a smoother of the empirical distribution function, the log-concave distribution function estimator reduces estimation variability to a much greater extent than it introduces bias. As a consequence, Monte Carlo simulations demonstrate that the smoothed version of the estimators are well superior to their non-smoothed counterparts, in terms of mean-squared error.     

用工业CT技术测量储层岩芯饱和度分布

认识储层岩石中含油饱和度及饱和度分布,对驱替机理的深入研究是非常重要的。为了搞清储层岩石在驱替过程中的饱和度分布情况,应用工业CT技术,提出了一种储层含油岩芯被驱替后的饱和度分布的CT密度差测量方法。在岩样的同一断面,分别对干岩样、饱和岩样及在驱替后的岩样进行CT扫描,重建相应的断层图象,测量所建图象的灰度值,计算出相应的密度值,用密度差法计算出饱和度及其分布值。在γ射线工业CT机“CD-300BG”上对某油田岩样进行了实际测量,获得的结果说明,采用CT密度差法测量饱和度分布是有效的。该方法与常规驱替法相比较,具有快速、精度高、无损岩样和能模拟地层状态测量等特点,是油田开发、油藏描述和地层评价的一种新的有效方法。     

Socially organized sentiments: Exploring the link between religious density and protest mobilization, 1960–1995

Extensive research has shown individual religiosity to have an impact upon U.S. protest participation. But very little work has examined the role of religious density in a community on the likelihood of protest mobilization. Our research links the religious density across 62 counties in New York State to various protest mobilization issues during the period of 1960–1995. In this research, we develop a theory of socially organized sentiments to examine religious influences on overall protest event mobilizations in local communities, a specific example of a more general theory that can link community structure to multiple forms of civic engagement. The impact of various religious traditions is assessed by using measures for the density of religious population per congregation of three religious traditions—Mainline Protestantism, Evangelical Protestantism and Catholicism. The analysis also assesses the likelihood of mobilization concerning four specific issues—African-American civil rights, gender, anti-nuclear/peace, and anti-poverty movements.