Cryptosporidium Dose Response Studies: Variation Between Isolates

The infectivity of three different isolates of the waterborne protozoan parasite Cryptosporidium parvum has been tested in human feeding studies. These three isolates (Iowa, TAMU, and UCP) have different ID50s, indicating substantial variation in their infectivity for humans. This finding is of great importance for quantitative risk assessment as it provides strong evidence for heterogeneity in infectivity among isolates of the same species.     

Cure rate models: A unified approach

The authors propose a novel class of cure rate models for right‐censored failure time data. The class is formulated through a transformation on the unknown population survival function. It includes the mixture cure model and the promotion time cure model as two special cases. The authors propose a general form of the covariate structure which automatically satisfies an inherent parameter constraint and includes the corresponding binomial and exponential covariate structures in the two main formulations of cure models. The proposed class provides a natural link between the mixture and the promotion time cure models, and it offers a wide variety of new modelling structures as well. Within the Bayesian paradigm, a Markov chain Monte Carlo computational scheme is implemented for sampling from the full conditional distributions of the parameters. Model selection is based on the conditional predictive ordinate criterion. The use of the new class of models is illustrated with a set of real data involving a melanoma clinical trial.     

中医治疗面神经炎疗效分析

在西医病辨和中医辨证基础上,运用针灸和中药相结合,治疗面神经炎20例,取得良好疗效。     

Non parametric analysis of gap times for bivariate recurrent event data with cure fraction

Recurrent event data often arise in longitudinal studies. In many applications, subjects may experience two different types of events alternatively over time or a pair of subjects may experience recurrent events of the same type. Medical advances have made it possible for some patients to be cured such that the disease of interest does not recur. In this article, we consider non parametric analysis of bivariate recurrent event data with cure fraction. Using the inverse-probability weighted (IPW) approach, we propose non parametric estimators for the proportion of cured patients and for the joint distribution functions of bivariate recurrence times of the uncured ones. The asymptotic properties of the proposed estimators are established. Simulation study indicates that the proposed estimators perform well in finite samples.     

A composite class of estimators using scrambled response mechanism for sensitive population mean in successive sampling

This paper considers the problem of estimation of population mean of a sensitive characteristics using non-sensitive auxiliary variable at current move in two move successive sampling. The proposed estimator is studied under five different scrambled response models. Various estimators have been elaborated to be the member of the proposed class of estimators. The properties of the proposed estimators have been analysed. Many estimators belonging to the proposed class have been explored under five scrambled response models. In order to identify the scrambled model effect, the proposed composite class of estimators is compared to the direct methods. Respondents privacy protection have also been elaborated under different models. Theoretical results are supplemented with numerical demonstrations using real data. Simulation has been carried out to show the applicability of proposed estimators and hence suitable recommendations are forwarded.     

Markov-Correlated Poisson Processes

In this article, we present a simple generalization of the Bernoulli trials model to a Markov chain with an additional parameter that measures dependence. We then formulate a Markov correlated Poisson process which, due to its flexibility, has great potential for analyzing many practical processes including those for long-term survival analysis.     

Standard Exponential Cure Rate Model with Noninformative or Informative Uniform-Exponential Censoring

In survival data analysis it is frequent the occurrence of a significant amount of censoring to the right indicating that there may be a proportion of individuals in the study for which the event of interest will never happen. This fact is not considered by the ordinary survival theory. Consequently, the survival models with a cure fraction have been receiving a lot of attention in the recent years. In this article, we consider the standard mixture cure rate model where a fraction p ₀ of the population is of individuals cured or immune and the remaining 1 ? p ₀ are not cured. We assume an exponential distribution for the survival time and an uniform-exponential for the censoring time. In a simulation study, the impact caused by the informative uniform-exponential censoring on the coverage probabilities and lengths of asymptotic confidence intervals is analyzed by using the Fisher information and observed information matrices.     

西部12省区经济发展的敛散性及指示功能研究

运用非线性映射方法对国务院西部地区开发领导小组办公室公布的1995年-2004年西部12省区的20个主要经济评价指标进行降维处理后,基于分形理论,研究了各年度的样本点之间的空间分布状态特征的关联维数。结果表明,2000年-2004年的关联维数分别为1.475,1.381,1.300,1.237,1.228,呈现减小的变动趋势,西部12省区之间的发展具有收敛性特征。文章最后讨论了西部12省区之间的区域经济发展收敛特性的指示功能。     

Nonparametric estimation of the sojourn time distributions for a multipath model

Summary. We use a multipath (multistate) model to describe data with multiple end points. Statistical inference based on the intermediate end point is challenging because of the problems of nonidentifiability and dependent censoring. We study nonparametric estimation for the path probability and the sojourn time distributions between the states. The methodology proposed can be applied to analyse cure models which account for the competing risk of death. Asymptotic properties of the estimators proposed are derived. Simulation shows that the methods proposed have good finite sample performance. The methodology is applied to two data sets.